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Performance of computer-aided diagnosis for colorectal sessile serrated lesions:A systematic review and meta-analysis 认领 引用
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作者 Song Zhang Shi-Hang Wang +11 位作者 You-Dong Zhao Jia-Hui Wei Xiang-Yu Sui Xin Li Huan-Wei Zhang Zhi-YaoHuang Cheng-Long Wang Hao Hu Jing Zhang Zhao-Shen Li Sheng-Bing Zhao Yu Bai 《World Journal of Gastroenterology》 SCIE CAS 2026年第27期160-172,共13页
BACKGROUND The efficacy of computer-aided diagnosis(CADx)systems in identifying sessile serrated lesions(SSLs),which are critical precancerous lesions in colorectal cancer,remains unclear.AIM To comprehensively evalua... BACKGROUND The efficacy of computer-aided diagnosis(CADx)systems in identifying sessile serrated lesions(SSLs),which are critical precancerous lesions in colorectal cancer,remains unclear.AIM To comprehensively evaluate the diagnostic performance of CADx systems in differentiating between SSLs and non-SSLs and hyperplastic polyps(HPs).METHODS MEDLINE,EMBASE,and the Cochrane Library were searched up to 11 June 2025 for studies evaluating the performance of CADx systems in differentiating SSLs.The primary outcomes were the pooled diagnostic accuracy,sensitivity,and specificity of the CADx systems in distinguishing SSLs from non-SSLs or HPs.RESULTS Nine studies encompassing 2915 images and 746 videos on SSL differentiation were included.For SSLs vs non-SSLs,the CADx system demonstrated an overall area under the curve(AUC)of 0.93,66% sensitivity,95% specificity,a positive predictive value(PPV)of 0.56,a negative predictive value(NPV)of 0.96,a positive likelihood ratio(LR+)of 12.3,and a negative likelihood ratio(LR-)of 0.36.For SSLs vs HPs,the overall AUC was 0.64,with 55% sensitivity,64% specificity,a PPV of 0.40,an NPV of 0.80,an LR+of 1.5,and an LR-of 0.70.The sensitivity analysis indicated stable findings,whereas the latest World Health Organization pathological standards,image classification algorithms(ICAs),real-time scenarios,multicenter settings and narrow band imaging(NBI)significantly affected CADx system sensitivity.ICA served as an independent factor influencing the sensitivity of differentiating between SSLs and non-SSLs[odds ratio(OR)=14.13],whereas NBI was an independent factor influencing the sensitivity of differentiating between SSLs and HPs(OR=7.27)according to multivariate meta-regression.CONCLUSION Current CADx systems cannot adequately differentiate SSLs from non-SSLs or HPs.Future development should focus on improving the differentiation capability and sensitivity of SSLs. 展开更多
关键词 Computer-aided diagnosis Sessile serrated lesions Colonoscopy Diagnostic accuracy Sensitivity Specificity
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Availability and use of computer-aided detection during colonoscopy:A real-world observational study at an Australian tertiary center 认领 引用
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作者 Vikram Rao Nirbaanjot Walia +7 位作者 Nikita Parkash Teagan Wanigaratne Suzannah Henshaw Gordon Chen Sheng Wei Lo Kim Hay Be Marcus Robertson Leonardo Zorron Cheng Tao Pu 《World Journal of Gastroenterology》 SCIE CAS 2026年第4期32-41,共10页
BACKGROUND One of the main aims of colonoscopy is to detect and remove precancerous polyps.Multiple studies have shown that computer-aided detection(CADe)technology enhances key metrics,including adenoma detection rat... BACKGROUND One of the main aims of colonoscopy is to detect and remove precancerous polyps.Multiple studies have shown that computer-aided detection(CADe)technology enhances key metrics,including adenoma detection rate(ADR),among endoscopists with low baseline detection rates.However,these findings largely come from controlled prospective studies where CADe is systematically used and endoscopists are aware they are being monitored for such metrics,bringing inherent biases.In Australia,CADe implementation is not yet standard practice,and its availability varies across endoscopy centers.We hypothesized that greater endoscopist use of CADe would be associated with higher ADR in real-world clinical settings.AIM To evaluate how varying levels of endoscopist use of CADe affect adenoma detection and other colonoscopy quality metrics in a tertiary Australian center,where CADe was available for all elective procedures from 2023.METHODS A single-center retrospective cohort study was conducted at a tertiary Australian center after introduction of the Olympus Endo-AID®CADe module in July 2023,available for all elective procedures.Colonoscopy reports from six months before and after implementation were reviewed.Endoscopists were grouped by observed CADe usage.The primary outcome was change in ADR by group.Secondary outcomes included sessile serrated lesion detection rate(SSL-DR),adenomas per patient(APP),and sessile serrated lesions per patient(SPP).RESULTS Seven endoscopists performed 636 pre-CADe and 386 post-CADe colonoscopies.Two endoscopists used CADe 100%of the time,four used it 50%-99%,and one did not use CADe.No endoscopists used CADe 1%-50%of the time.ADR significantly improved from 29%to 41.9%in the 50%-99%group(odds ratio 1.77,95%CI:1.13-2.75,P=0.01).No ADR change was observed in the 100%group,which had a baseline ADR above 60%,although APP increased from 0.90 to 2.08(relative risk 2.31,95%CI:1.97-2.73,P<0.0001).SSL-DR and SPP were not significantly affected by CADe.CONCLUSION In this real-world study,the availability of CADe was associated with an uptake by the majority of the endoscopists and led to significant improvement in ADR even when not being used in all procedures.Similarly to previous studies,no such benefit was observed for endoscopists who had a high baseline ADR.However,endoscopists with high baseline ADR did improve their APP after introduction of CADe.In addition,CADe availability did not improve SSL-DR across the cohort.This real-world significant increase from moderate baseline ADR reinforces its benefit when adopted in routine clinical practice. 展开更多
关键词 Computer-aided detection Adenoma detection rate Colonoscopy Artificial intelligence Endoscopy Screening,surveillance Colorectal neoplasm Polyp Adenoma
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Bridging the gap:Computer-aided detection and Yamada classification system matches expert performance 认领 引用
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作者 Lin Qiu Jian Ding +23 位作者 Chun-Xiao Lai Hui Yang Feng Li Zhi-Jian Li Wen Wu Gui-Ming Liu Quan-Sheng Guan Xi-Gang Zhang Rui-Ya Zhang Li-Zhi Yi Zhi-Fang Zhao Lv Deng Wei-Jian Lun Zhen-Yu Wang Wei-Ming Lu Wei-Guang Qiao Su-Ling Wang Si-Mei Chen Wen-Qian Shen Li-Min Cheng Ben-Gui Zhu Shun-Hui He Jie Dai Yang Bai 《World Journal of Gastroenterology》 SCIE CAS 2025年第40期86-96,共11页
BACKGROUND Computer-aided diagnosis(CAD)may assist endoscopists in identifying and classifying polyps during colonoscopy for detecting colorectal cancer.AIM To build a system using CAD to detect and classify polyps ba... BACKGROUND Computer-aided diagnosis(CAD)may assist endoscopists in identifying and classifying polyps during colonoscopy for detecting colorectal cancer.AIM To build a system using CAD to detect and classify polyps based on the Yamada classification.METHODS A total of 24045 polyp and 72367 nonpolyp images were obtained.We established a computer-aided detection and Yamada classification model based on the YOLOv7 neural network algorithm.Frame-based and image-based evaluation metrics were employed to assess the performance.RESULTS Computer-aided detection and Yamada classification screened polyps with a precision of 96.7%,a recall of 95.8%,and an F1-score of 96.2%,outperforming those of all groups of endoscopists.In regard to the Yamada classification of polyps,the CAD system displayed a precision of 82.3%,a recall of 78.5%,and an F1-score of 80.2%,outper-forming all levels of endoscopists.In addition,according to the image-based method,the CAD had an accuracy of 99.2%,a specificity of 99.5%,a sensitivity of 98.5%,a positive predictive value of 99.0%,a negative predictive value of 99.2%for polyp detection and an accuracy of 97.2%,a specificity of 98.4%,a sensitivity of 79.2%,a positive predictive value of 83.0%,and a negative predictive value of 98.4%for poly Yamada classification.CONCLUSION We developed a novel CAD system based on a deep neural network for polyp detection,and the Yamada classi-fication outperformed that of nonexpert endoscopists.This CAD system could help community-based hospitals enhance their effectiveness in polyp detection and classification. 展开更多
关键词 Yamada classification Endoscopy Deep learning Artificial intelligence Computer-aided diagnosis
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Neonatal Jaundice Detection:A Comprehensive Survey from Manual to Computer-Aided Methods 认领 引用
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作者 Navdeep Kaur Ajay Mittal Aastha Gupta 《Journal of Bionic Engineering》 SCIE EI CSCD 2025年第6期2774-2804,共31页
Jaundice,common condition in newborns,is characterized by yellowing of the skin and eyes due to elevated levels of bilirubin in the blood.Timely detection and management of jaundice are crucial to prevent potential co... Jaundice,common condition in newborns,is characterized by yellowing of the skin and eyes due to elevated levels of bilirubin in the blood.Timely detection and management of jaundice are crucial to prevent potential complications.Traditional jaundice assessment methods rely on visual inspection or invasive blood tests that are subjective and painful for infants,respectively.Although several automated methods for jaundice detection have been developed during the past few years,a limited number of reviews consolidating these developments have been presented till date,making it essential to systematically evaluate and present the existing advancements.This paper fills this gap by providing a thorough survey of automated methods for jaundice detection in neonates.The primary focus of the survey is to review the existing methodologies,techniques,and technologies used for neonatal jaundice detection.The key findings from the review indicate that image-based bilirubinometers and transcutaneous bilirubinometers are promising non-invasive alternatives,and provide a good trade-off between accuracy and ease of use.However,their effectiveness varies with factors like skin pigmentation,gestational age,and measurement site.Spectroscopic and biosensor-based techniques show high sensitivity but need further clinical validation.Despite advancements,several challenges including device calibration,large-scale validation,and regulatory barriers still haunt the researchers.Standardization,regulatory compliances,and seamless integration into healthcare workflows are the key hurdles to be addressed.By consolidating the current knowledge and discussing the challenges and opportunities in this field,this survey aims to contribute to the advancement of automatic jaundice detection and ultimately improve neonatal care. 展开更多
关键词 Automated jaundice detection Bilirubin estimation Bilirubinometers Computer-aided diagnosis Hyperbilirubinemia Jaundice Neonates
Diagnostic value of real-time computer-aided detection for precancerous lesion during esophagogastroduodenoscopy:A metaanalysis 认领 引用
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作者 Zong-Yang Li Ya-Hui Liu Hong-Qiao Cai 《World Journal of Gastrointestinal Surgery》 SCIE 2025年第11期473-488,共16页
BACKGROUND Early detection of precancerous lesions is of vital importance for reducing the incidence and mortality of upper gastrointestinal(UGI)tract cancer.However,traditional endoscopy has certain limitations in de... BACKGROUND Early detection of precancerous lesions is of vital importance for reducing the incidence and mortality of upper gastrointestinal(UGI)tract cancer.However,traditional endoscopy has certain limitations in detecting precancerous lesions.In contrast,real-time computer-aided detection(CAD)systems enhanced by artificial intelligence(AI)systems,although they may increase unnecessary medical procedures,can provide immediate feedback during examination,thereby improving the accuracy of lesion detection.This article aims to conduct a meta-analysis of the diagnostic performance of CAD systems in identifying precancerous lesions of UGI tract cancer during esophagogastroduodenoscopy(EGD),evaluate their potential clinical application value,and determine the direction for further research.AIM To investigate the improvement of the efficiency of EGD examination by the realtime AI-enabled real-time CAD system(AI-CAD)system.METHODS PubMed,EMBASE,Web of Science and Cochrane Library databases were searched by two independent reviewers to retrieve literature with per-patient analysis with a deadline up until April 2025.A meta-analysis was performed with R Studio software(R4.5.0).A random-effects model was used and subgroup analysis was carried out to identify possible sources of heterogeneity.RESULTS The initial search identified 802 articles.According to the inclusion criteria,2113 patients from 10 studies were included in this meta-analysis.The pooled accuracy difference,logarithmic difference of diagnostic odds ratios,sensitivity,specificity and the area under the summary receiver operating characteristic curve(area under the curve)of both AI group and endoscopist group for detecting precancerous lesion were 0.16(95%CI:0.12-0.20),-0.19(95%CI:-0.75-0.37),0.89(95%CI:0.85-0.92,AI group),0.67(95%CI:0.63-0.71,endoscopist group),0.89(95%CI:0.84-0.93,AI group),0.77(95%CI:0.70-0.83,endoscopist group),0.928(95%CI:0.841-0.948,AI group),0.722(95%CI:0.677-0.821,endoscopist group),respectively.CONCLUSION The present studies further provide evidence that the AI-CAD is a reliable endoscopic diagnostic tool that can be used to assist endoscopists in detection of precancerous lesions in the UGI tract.It may be introduced on a large scale for clinical application to enhance the accuracy of detecting precancerous lesions in the UGI tract. 展开更多
关键词 Artificial intelligence Real-time computer-aided detection system Precancerous lesion Esophagogastroduodenoscopy Endoscopy Upper gastrointestinal tract Diagnostic performance Meta-analysis
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Research on the Application of AI Computer-Aided Diagnosis in Dermatology 认领 引用
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作者 Xiaochun Zhang 《Journal of Clinical and Nursing Research》 2025年第12期105-110,共6页
With the development of artificial intelligence technology,AI computer-aided diagnosis has found certain applications in the field of dermatology.However,due to the vast variety and complex manifestations of skin dise... With the development of artificial intelligence technology,AI computer-aided diagnosis has found certain applications in the field of dermatology.However,due to the vast variety and complex manifestations of skin diseases,the specific mechanisms underlying AI computer-aided diagnosis in this context still require further exploration.Therefore,this paper,based on the imaging characteristics of skin diseases,elucidates the technical principles of AI computer-aided diagnosis and analyzes the practical application effects of AI in the diagnostic process of skin diseases.This provides new data support and methodological foundations for clinical teaching and research on skin diseases. 展开更多
关键词 AI computer-aided Skin disease diagnosis Image recognition Deep learning Intelligent healthcare
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Using shapes correlation for active contour segmentation of uterine fibroid ultrasound images in computer-aided therapy 认领 引用 被引量：14
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作者 NI Bo HE Fa-zhi +1 位作者 PAN Yi-teng YUAN Zhi-yong 《Applied Mathematics(A Journal of Chinese Universities)》 SCIE CSCD 2016年第1期37-52,共16页
Segmenting the lesion regions from the ultrasound （US） images is an important step in the intra-operative planning of some computer-aided therapies. High-Intensity Focused Ultrasound （HIFU）, as a popular computer-... Segmenting the lesion regions from the ultrasound （US） images is an important step in the intra-operative planning of some computer-aided therapies. High-Intensity Focused Ultrasound （HIFU）, as a popular computer-aided therapy, has been widely used in the treatment of uterine fibroids. However, such segmentation in HIFU remains challenge for two reasons： （1） the blurry or missing boundaries of lesion regions in the HIFU images and （2） the deformation of uterine fibroids caused by the patient＇s breathing or an external force during the US imaging process, which can lead to complex shapes of lesion regions. These factors have prevented classical active contour-based segmentation methods from yielding desired results for uterine fibroids in US images. In this paper, a novel active contour-based segmentation method is proposed, which utilizes the correlation information of target shapes among a sequence of images as prior knowledge to aid the existing active contour method. This prior knowledge can be interpreted as a unsupervised clustering of shapes prior modeling. Meanwhile, it is also proved that the shapes correlation has the low-rank property in a linear space, and the theory of matrix recovery is used as an effective tool to impose the proposed prior on an existing active contour model. Finally, an accurate method is developed to solve the proposed model by using the Augmented Lagrange Multiplier （ALM）. Experimental results from both synthetic and clinical uterine fibroids US image sequences demonstrate that the proposed method can consistently improve the performance of active contour models and increase the robustness against missing or misleading boundaries, and can greatly improve the efficiency of HIFU therapy. 展开更多
关键词 Active contour shapes correlation ultrasound image segmentation matrix recovery computer-aided therapy.
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Computer-aided diagnosis of retinopathy based on vision transformer 认领 引用 被引量：5
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作者 Zhencun Jiang Lingyang Wang +4 位作者 Qixin Wu Yilei Shao Meixiao Shen Wenping Jiang Cuixia Dai 《Journal of Innovative Optical Health Sciences》 SCIE EI CSCD 2022年第2期49-57,共9页
Age-related Macular Degeneration(AMD)and Diabetic Macular Edema(DME)are two com-mon retinal diseases for elder people that may ultimately cause irreversible blindness.Timely and accurate diagnosis is essential for the... Age-related Macular Degeneration(AMD)and Diabetic Macular Edema(DME)are two com-mon retinal diseases for elder people that may ultimately cause irreversible blindness.Timely and accurate diagnosis is essential for the treatment of these diseases.In recent years,computer-aided diagnosis(CAD)has been deeply investigated and effectively used for rapid and early diagnosis.In this paper,we proposed a method of CAD using vision transformer to analyze optical co-herence tomography(OCT)images and to automatically discriminate AMD,DME,and normal eyes.A classification accuracy of 99.69%was achieved.After the model pruning,the recognition time reached 0.010 s and the classification accuracy did not drop.Compared with the Con-volutional Neural Network(CNN)image classification models(VGG16,Resnet50,Densenet121,and EfficientNet),vision transformer after pruning exhibited better recognition ability.Results show that vision transformer is an improved alternative to diagnose retinal diseases more accurately. 展开更多
关键词 Vision transformer OCT image classi¯cation retinopathy computer-aided diagnosis model pruning
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A computer-aided chem-photodynamic drugs self-delivery system for synergistically enhanced cancer therapy 认领 引用 被引量：4
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作者 Qiu Wang Mengchi Sun +6 位作者 Chang Li Dan Li Zimeng Yang Qikun Jiang Zhonggui He Huaiwei Ding Jin Sun 《Asian Journal of Pharmaceutical Sciences》 SCIE CAS 2021年第2期203-212,共10页
The therapeutic strategy that gives consideration to the combination of photodynamic therapy and chemotherapy,has emerged as a potential development of effective anti-cancer medicine.Nevertheless,co-delivery of photos... The therapeutic strategy that gives consideration to the combination of photodynamic therapy and chemotherapy,has emerged as a potential development of effective anti-cancer medicine.Nevertheless,co-delivery of photosensitizers(PSs)and chemotherapeutic drugs in traditional carriers still remains great limitations due to low drug loadings and poor biocompatibility.Herein,we have utilized a computer-aided strategy to achieve a desired carrier-free self-delivery of pyropheophorbide a(PPa,a common PS)and podophyllotoxin(PPT,a classical chemotherapeutic drug)for synergistic cancer therapy.First,the computational simulation method identified the similar molecular sizes and rigid molecular structures between two drugs molecules.Based on the molecular docking,the intermolecular interactions were found to includeπ-πstackings,hydrophobic interactions and hydrogen bonds.Next,both drugs could co-assemble into nanoparticles(NPs)via one-step nanoprecipitation method.The various spectral experiments(UV,IR and FL)were conducted to evaluate the formation mechanism of spherical NPs.Moreover,in vitro and in vivo experiments systematically demonstrated that PPT/PPa NPs not only showed better cellular uptake efficiency,stronger cytotoxicity and higher accumulation in tumor sites,but also exhibited synergistic antitumor effect in female BALB/C bearing-4T1 tumor mice.Such a computer-aided design strategy of chem-photodynamic drugs self-delivery systems pave the way for efficient synergistic cancer therapy. 展开更多
关键词 Photodynamic therapy Chemotherapy Self-delivery Computer-aided Synergistic cancer therapy
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Computer-aided texture analysis combined with experts' knowledge: Improving endoscopic celiac disease diagnosis 认领 引用 被引量：3
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作者 Michael Gadermayr Hubert Kogler +3 位作者 Maximilian Karla Dorit Merhof Andreas Uhl Andreas Vécsei 《World Journal of Gastroenterology》 SCIE CAS 2016年第31期7124-7134,共11页
AIM: To further improve the endoscopic detection of intestinal mucosa alterations due to celiac disease(CD).METHODS: We assessed a hybrid approach based on the integration of expert knowledge into the computerbased cl... AIM: To further improve the endoscopic detection of intestinal mucosa alterations due to celiac disease(CD).METHODS: We assessed a hybrid approach based on the integration of expert knowledge into the computerbased classification pipeline. A total of 2835 endoscopic images from the duodenum were recorded in 290 children using the modified immersion technique(MIT). These children underwent routine upper endoscopy for suspected CD or non-celiac upper abdominal symptoms between August 2008 and December 2014. Blinded to the clinical data and biopsy results, three medical experts visually classified each image as normal mucosa(Marsh-0) or villous atrophy(Marsh-3). The experts' decisions were further integrated into state-of-the-arttexture recognition systems. Using the biopsy results as the reference standard, the classification accuracies of this hybrid approach were compared to the experts' diagnoses in 27 different settings.RESULTS: Compared to the experts' diagnoses, in 24 of 27 classification settings(consisting of three imaging modalities, three endoscopists and three classification approaches), the best overall classification accuracies were obtained with the new hybrid approach. In 17 of 24 classification settings, the improvements achieved with the hybrid approach were statistically significant(P < 0.05). Using the hybrid approach classification accuracies between 94% and 100% were obtained. Whereas the improvements are only moderate in the case of the most experienced expert, the results of the less experienced expert could be improved significantly in 17 out of 18 classification settings. Furthermore, the lowest classification accuracy, based on the combination of one database and one specific expert, could be improved from 80% to 95%(P < 0.001).CONCLUSION: The overall classification performance of medical experts, especially less experienced experts, can be boosted significantly by integrating expert knowledge into computer-aided diagnosis systems. 展开更多
关键词 Celiac disease Diagnosis endoscopy Computer-aided texture analysis Biopsy Pattern recognition
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Enhanced characterization of solid solitary pulmonary nodules with Bayesian analysis-based computer-aided diagnosis 认领 引用 被引量：5
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作者 Simone Perandini Gian Alberto Soardi +9 位作者 Massimiliano Motton Raffaele Augelli Chiara Dallaserra Gino Puntel Arianna Rossi Giuseppe Sala Manuel Signorini Laura Spezia Federico Zamboni Stefania Montemezzi 《World Journal of Radiology》 2016年第8期729-734,共6页
The aim of this study was to prospectively assess the accuracy gain of Bayesian analysis-based computeraided diagnosis(CAD) vs human judgment alone in characterizing solitary pulmonary nodules(SPNs) at computed tomogr... The aim of this study was to prospectively assess the accuracy gain of Bayesian analysis-based computeraided diagnosis(CAD) vs human judgment alone in characterizing solitary pulmonary nodules(SPNs) at computed tomography(CT). The study included 100 randomly selected SPNs with a definitive diagnosis. Nodule features at first and follow-up CT scans as well as clinical data were evaluated individually on a 1 to 5 points risk chart by 7 radiologists, firstly blinded then aware of Bayesian Inference Malignancy Calculator(BIMC) model predictions. Raters' predictions were evaluated by means of receiver operating characteristic(ROC) curve analysis and decision analysis. Overall ROC area under the curve was 0.758 before and 0.803 after the disclosure of CAD predictions(P = 0.003). A net gain in diagnostic accuracy was found in 6 out of 7 readers. Mean risk class of benign nodules dropped from 2.48 to 2.29, while mean risk class of malignancies rose from 3.66 to 3.92. Awareness of CAD predictions also determined a significant drop on mean indeterminate SPNs(15 vs 23.86 SPNs) and raised the mean number of correct and confident diagnoses(mean 39.57 vs 25.71 SPNs). This study provides evidence supporting the integration of the Bayesian analysis-based BIMC model in SPN characterization. 展开更多
关键词 Solitary pulmonary nodule Computer-aided diagnosis Lung neoplasms Multidetector computed tomography Bayesian prediction
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Computer-Aided Design of Some Advanced Steels and Cemented Carbides 认领 引用 被引量：2
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作者 LI Lin ZHANG Mei +2 位作者 HE Yan-lin De Cooman Bruno Wollants Patrick 《Journal of Iron and Steel Research International》 SCIE CAS 2005年第6期42-48,共7页
Thermodynamic and kinetic study on TRIP （transformation induced plasticity） steels, cemented carbides and mold steel for plastics were carried out in order to design modern advanced materials. With the sublattice mo... Thermodynamic and kinetic study on TRIP （transformation induced plasticity） steels, cemented carbides and mold steel for plastics were carried out in order to design modern advanced materials. With the sublattice model, equilibrium compositions of ferrite and austenite phases in TRIP steels, as well as volume fraction of austenite at inter-critical temperatures for different time were calculated. Concentration profiles of carbon, manganese, aluminum and silicon in the steels were also estimated in the lattice fixed frame of reference. The effect of Si and Mn on TRIP was discussed according to thermodynamic and kinetic analyses. In order to understand and produce the graded nanophase structure of cemented carbides, miscellaneous phases in the M-Co-C （M= Ti, Ta, Nh） systems and Co-V-C system were modeled. Solution parameters and thermodynamic： properties were listed in detail. The improvement of machining behavior of prehardened mould steel for plastics was obtained by computer-aided composition design. The results showed that the matrix composition of large-section prehardened mould steel for plastic markedly influences the precipitation of non-metallic inclusion and the composition control by the aid of Thermo-Calc software package minimizes the amount of detrimental oxide inclusion. In addition, the modification of calcium was optimized in composition design. 展开更多
关键词 computer-aided composition design TRIP steel cemented carbide prehardened mould steel concentration profile thermodynamic kinetic equilibrium composition
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A Novel Human Antibody,HF,against HER2/erb-B2 Obtained by a Computer-Aided Antibody Design Method 认领 引用 被引量：2
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作者 Chunxia Qiao Ming Lv +8 位作者 Xinying Li Xiaoling Lang Shouqin Lv Mian Long Yan Li Shusheng Geng Zhou Lin Beifen Shen Jiannan Feng 《Engineering》 SCIE EI CAS CSCD 2021年第11期1566-1576,共11页
Fully human antibodies have minimal immunogenicity and safety profiles.At present,most potential antibody drugs in clinical trials are humanized or fully human.Human antibodies are mostly generated using the phage dis... Fully human antibodies have minimal immunogenicity and safety profiles.At present,most potential antibody drugs in clinical trials are humanized or fully human.Human antibodies are mostly generated using the phage display method(in vitro)or by transgenic mice(in vivo);other methods include B lymphocyte immortalization,human–human hybridoma,and single-cell polymerase chain reaction.Here,we describe a structure-based computer-aided de novo design technology for human antibody generation.Based on the complex structure of human epidermal growth factor receptor 2(HER2)/Herceptin,we first designed six short peptides targeting the potential epitope of HER2 recognized by Herceptin.Next,these peptides were set as complementarity determining regions in a suitable immunoglobulin frame,giving birth to a novel anti-HER2 antibody named "HF,"which possessed higher affinity and more effective anti-tumor activity than Herceptin.Our work offers a useful tool for the quick design and selection of novel human antibodies for basic mechanical research as well as for imaging and clinical applications in immune-related diseases,such as cancer and infectious diseases. 展开更多
关键词 HER2/erb-B2 Human antibody Computer-aided design
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The computer-aided design method of cabinet based on style imagery 认领 引用 被引量：2
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作者 沈张帆 薛澄岐 +3 位作者 王海燕 牛亚峰 邵将 张晶 《Journal of Southeast University(English Edition)》 EI CAS 2015年第3期369-374,共6页
Due to the practical problems of the high costs and the long development cycle of China’s cabinet production,a computer-aided design method of the cabinet based on style imagery is proposed.According to the principle... Due to the practical problems of the high costs and the long development cycle of China’s cabinet production,a computer-aided design method of the cabinet based on style imagery is proposed.According to the principle of the conjoint analysis method, the rough set theory and the weight coefficient of different components of the cabinet,a multi-dimensional model of style imagery to evaluate the cabinet is built. Then the related constants of style imagery are calculated and the cabinet components library is also built by the three-dimensional modeling.Finally,with recombinant technology and the mapping model between cabinet style and external characteristics,the prototype system based on Visual Studio is proposed.This system actualizes the bidirectional reasoning between product style imagery and the shape features,which can assist designers to produce more creative designs,greatly improve the efficiency of cabinet development and increase the profits of companies. 展开更多
关键词 cabinet computer-aided design style imagery component recombinant shape features
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3D printed nerve guidance channels: computer-aided control of geometry, physical cues, biological supplements and gradients 认领 引用 被引量：4
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作者 Blake N.Johnson Xiaofeng Jia 《Neural Regeneration Research》 SCIE CAS CSCD 2016年第10期1568-1569,共2页
Nerve guidance channels for peripheral nerve injury： Over the past decade, nerve guidance channels （NGCs） have emerged as a promising technology for regenerating gap injuries in peripheral nerves. Nerve gap injurie... Nerve guidance channels for peripheral nerve injury： Over the past decade, nerve guidance channels （NGCs） have emerged as a promising technology for regenerating gap injuries in peripheral nerves. Nerve gap injuries resulting from neurodegeneration and trauma, such as car accidents and battlefield wounds, affect hun- dreds of thousands of people annually. Motivated by suboptimal results obtained with the current gold standard of autologous grafting （i.e., autografts）, various commercially available NGCs composed of synthetic and biomaterials are now alternatively available （Jia et al., 2014; Jones et al., 2016）. 展开更多
关键词 NGC physical cues printed nerve guidance channels biological supplements and gradients computer-aided control of geometry
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Computer-aided diagnosis for contrast-enhanced ultrasound in the liver 认领 引用 被引量：2
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作者 Katsutoshi Sugimoto Junji Shiraishi +1 位作者 Fuminori Moriyasu Kunio Doi 《World Journal of Radiology》 2010年第6期215-223,共9页
Computer-aided diagnosis(CAD) has become one of the major research subjects in medical imaging and diagnostic radiology.The basic concept of CAD is to provide computer output as a second opinion to assist radiologists... Computer-aided diagnosis(CAD) has become one of the major research subjects in medical imaging and diagnostic radiology.The basic concept of CAD is to provide computer output as a second opinion to assist radiologists' image interpretations by improving the accuracy and consistency of radiologic diagnosis and also by reducing the image-reading time.To date,research on CAD in ultrasound(US)-based diagnosis has been carried out mostly for breast lesions and has been limited in the fields of gastroenterology and hepatology,with most studies being conducted using B-mode US images.Two CAD schemes with contrast-enhanced US(CEUS) that are used in classifying focal liver lesions(FLLs) as liver metastasis,hemangioma,or three histologically differentiated types of hepatocellular carcinoma(HCC) are introduced in this article:one is based on physicians' subjective pattern classifications(subjective analysis) and the other is a computerized scheme for classification of FLLs(quantitative analysis).Classification accuracies for FLLs for each CAD scheme were 84.8% and 88.5% for metastasis,93.3% and 93.8% for hemangioma,and 98.6% and 86.9% for all HCCs,respectively.In addition,the classification accuracies for histologic differentiation of HCCs were 65.2% and 79.2% for well-differentiated HCCs,41.7% and 50.0% for moderately differentiated HCCs,and 80.0% and 77.8% for poorly differentiated HCCs,respectively.There are a number of issues concerning the clinical application of CAD for CEUS,however,it is likely that CAD for CEUS of the liver will make great progress in the future. 展开更多
关键词 Computer-aided diagnosis Focal liver lesion Ultrasonography Contrast agent Micro-flow imaging
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Computer-aided designing and manufacturing of advanced steels 认领 引用 被引量：1
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作者 LI Lin HE Yanlin +3 位作者 B.C. De Cooman P. Wollants S. G. Huang J. Vleugels 《Rare Metals》 SCIE EI CAS 2006年第5期407-411,共5页
Suitable optimization and simulation were performed using a powerful software package with a mature database as well as modem measurement facilities, which led to the successful designing and manufacturing of advanced... Suitable optimization and simulation were performed using a powerful software package with a mature database as well as modem measurement facilities, which led to the successful designing and manufacturing of advanced steels. In the course of designing, the composition of a large section of prehardened mold steel for plastics was estimated so as to lower the quantities of oxide inclusions to change the type of carbides and to raise the machinability. The composition and process were adjusted to obtain satisfactory surface quality for the prevailing galvanization in transformation-induced plasticity （TRIP） steel. The refuting process of low-carbon steel was simulated in the light of both Thermo-Calc and Factsage. Thermodynamic and kinetic analyses were always conducted during the test and the procedure. 展开更多
关键词 material science advanced steel computer-aided design refining thermodynamics kinetics
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Improved computer-aided detection of pulmonary nodules via deep learning in the sinogram domain 认领 引用 被引量：1
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作者 Yongfeng Gao Jiaxing Tan +2 位作者 Zhengrong Liang Lihong Li Yumei Huo 《Visual Computing for Industry,Biomedicine,and Art》 EI 2019年第1期129-137,共9页
Computer aided detection(CADe)of pulmonary nodules plays an important role in assisting radiologists’diagnosis and alleviating interpretation burden for lung cancer.Current CADe systems,aiming at simulating radiologi... Computer aided detection(CADe)of pulmonary nodules plays an important role in assisting radiologists’diagnosis and alleviating interpretation burden for lung cancer.Current CADe systems,aiming at simulating radiologists’examination procedure,are built upon computer tomography(CT)images with feature extraction for detection and diagnosis.Human visual perception in CT image is reconstructed from sinogram,which is the original raw data acquired from CT scanner.In this work,different from the conventional image based CADe system,we propose a novel sinogram based CADe system in which the full projection information is used to explore additional effective features of nodules in the sinogram domain.Facing the challenges of limited research in this concept and unknown effective features in the sinogram domain,we design a new CADe system that utilizes the self-learning power of the convolutional neural network to learn and extract effective features from sinogram.The proposed system was validated on 208 patient cases from the publicly available online Lung Image Database Consortium database,with each case having at least one juxtapleural nodule annotation.Experimental results demonstrated that our proposed method obtained a value of 0.91 of the area under the curve(AUC)of receiver operating characteristic based on sinogram alone,comparing to 0.89 based on CT image alone.Moreover,a combination of sinogram and CT image could further improve the value of AUC to 0.92.This study indicates that pulmonary nodule detection in the sinogram domain is feasible with deep learning. 展开更多
关键词 Computer-aided detection Computed tomography Deep learning Lung Sinogram
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An Optimal Deep Learning Based Computer-Aided Diagnosis System for Diabetic Retinopathy 认领 引用 被引量：1
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作者 Phong Thanh Nguyen Vy Dang Bich Huynh +3 位作者 Khoa Dang Vo Phuong Thanh Phan Eunmok Yang Gyanendra Prasad Joshi 《Computers, Materials & Continua》 SCIE EI 2021年第3期2815-2830,共16页
Diabetic Retinopathy(DR)is a significant blinding disease that poses serious threat to human vision rapidly.Classification and severity grading of DR are difficult processes to accomplish.Traditionally,it depends on o... Diabetic Retinopathy(DR)is a significant blinding disease that poses serious threat to human vision rapidly.Classification and severity grading of DR are difficult processes to accomplish.Traditionally,it depends on ophthalmoscopically-visible symptoms of growing severity,which is then ranked in a stepwise scale from no retinopathy to various levels of DR severity.This paper presents an ensemble of Orthogonal Learning Particle Swarm Optimization(OPSO)algorithm-based Convolutional Neural Network(CNN)Model EOPSO-CNN in order to perform DR detection and grading.The proposed EOPSO-CNN model involves three main processes such as preprocessing,feature extraction,and classification.The proposed model initially involves preprocessing stage which removes the presence of noise in the input image.Then,the watershed algorithm is applied to segment the preprocessed images.Followed by,feature extraction takes place by leveraging EOPSO-CNN model.Finally,the extracted feature vectors are provided to a Decision Tree(DT)classifier to classify the DR images.The study experiments were carried out using Messidor DR Dataset and the results showed an extraordinary performance by the proposed method over compared methods in a considerable way.The simulation outcome offered the maximum classification with accuracy,sensitivity,and specificity values being 98.47%,96.43%,and 99.02%respectively. 展开更多
关键词 Diabetic retinopathy convolutional neural network classification image processing computer-aided diagnosis
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A Method for Solving Computer-Aided Product Design Optimization Problem Based on Back Propagation Neural Network 认领 引用 被引量：1
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作者 周祥 何小荣 陈丙珍 《Chinese Journal of Chemical Engineering》 SCIE EI CAS 2004年第4期510-514,共5页
Because of the powerful mapping ability, back propagation neural network (BP-NN) has been employed in computer-aided product design (CAPD) to establish the property prediction model. The backward problem in CAPD is to... Because of the powerful mapping ability, back propagation neural network (BP-NN) has been employed in computer-aided product design (CAPD) to establish the property prediction model. The backward problem in CAPD is to search for the appropriate structure or composition of the product with desired property, which is an optimization problem. In this paper, a global optimization method of using the a BB algorithm to solve the backward problem is presented. In particular, a convex lower bounding function is constructed for the objective function formulated with BP-NN model, and the calculation of the key parameter a is implemented by recurring to the interval Hessian matrix of the objective function. Two case studies involving the design of dopamine β-hydroxylase (DβH) inhibitors and linear low density polyethylene (LLDPE) nano composites are investigated using the proposed method. 展开更多
关键词 computer-aided product design (CAPD) back propagation neural network (BP-NN) a BB algorithm convex lower bounding function interval Hessian matrix
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