Explainable AI for Interpretation of Ovarian Tumor Classification Using Enhanced ResNet50Article Published on 2024-07-192024-09-05 Journal: Diagnostics [Category] update2024, [키워드] custom ResNet50 explainable AI methods grad-CAM interpretable AI LIME occlusion analysis saliency map SHAP SmoothGrad [DOI] 10.3390/diagnostics14141567 PMC 바로가기 [Article Type] Article
An explainable AI-based blood cell classification using optimized convolutional neural networkOriginal Research Article Published on 2024-07-022024-09-05 Journal: Journal of Pathology Informatics [Category] update2024, [키워드] Explainable AI GRAD- CAM LIME Optimized CNN SHAP transfer learning White blood cells [DOI] 10.1016/j.jpi.2024.100389 PMC 바로가기 [Article Type] Original Research Article
Explainable artificial intelligence model for identifying COVID-19 gene biomarkersArticle Published on 2023-02-012024-09-05 Journal: Computers in biology and medicine [Category] update2024, [키워드] COVID-19 Explainable artificial intelligence LIME SHAP XGBoost [DOI] 10.1016/j.compbiomed.2023.106619 PMC 바로가기 [Article Type] Article
Occurrence of viruses in sewage sludge: A systematic review하수슬러지 내 바이러스 발생: 체계적 고찰Review Published on 2022-06-102022-09-11 Journal: The Science of the total environment [Category] COVID19(2023년), SARS, 치료기술, [키워드] acute respiratory syndrome acute respiratory syndrome coronavirus acute respiratory syndrome coronavirus 2 Adenovirus Biosolids Combination combinations Concentration Contamination coronavirus COVID-19 epidemic digested dissemination enteric enteric virus Enteric viruses enterovirus Health Hepatitis hepatitis A hepatitis A virus in viral include infected individuals infectious dose information ingestion intake LIME lowest Norovirus occur Particle Prevalence prevalent reported reveal risk rotavirus SARS-CoV-2 searched severe acute respiratory syndrome Coronavirus Sewage sludge Sludge sludge treatment Soil Surface water Surveillance survival systematic review Treatment viral infection Viral particles virus viruses wastewater water Web of Science [DOI] 10.1016/j.scitotenv.2022.153886 PMC 바로가기 [Article Type] Review
Wearable Devices, Smartphones, and Interpretable Artificial Intelligence in Combating COVID-19COVID-19 퇴치를 위한 웨어러블 기기, 스마트폰 및 해석 가능한 인공 지능Article Published on 2021-12-172022-09-10 Journal: Sensors (Basel, Switzerland) [Category] SARS, 치료기술, [키워드] abnormal change Accuracy affected approach artificial artificial intelligence collected combating COVID-19 COVID-19 detection dataset decision fusion Early detection Final generate Health health indicators heart rate heart rate variability HRV Infection Inflammation Inflammatory response intelligence Interpretation LIME Local log Measures minute natural language processing Patient Precision recall Recurrent Neural Network respiratory respiratory infection respiratory infections supported Symptom Variability wearables [DOI] 10.3390/s21248424 PMC 바로가기 [Article Type] Article
Explainable Artificial Intelligence for Bias Detection in COVID CT-Scan ClassifiersCOVID CT-Scan 분류기에서 편향 감지를 위한 설명 가능한 인공 지능Article Published on 2021-08-232022-09-10 Journal: Sensors (Basel, Switzerland) [Category] MERS, SARS, 치료기술, [키워드] Accuracy affected Analysis approach artificial artificial intelligence AUC Bia biases changes in Classifier classifiers Complete computer vision Computerized tomography COVID COVID 19 dataset detection drastic evaluated Explainable AI Explainable artificial intelligence Gradient heatmap help highlight identify image classification Impact intelligence LIME Medical imaging methodology motivation Performance metrics problem Result robust shown Smooth tandem Vanilla were used [DOI] 10.3390/s21165657 PMC 바로가기 [Article Type] Article
Prognostic Assessment of COVID-19 in the Intensive Care Unit by Machine Learning Methods: Model Development and ValidationOriginal Paper Published on 2020-11-112022-10-30 Journal: Journal of Medical Internet Research [Category] COVID-19, [키워드] actual risk addition Additive administer albumin Algorithm Algorithms Analysis assessment AUC calculator can be used characteristic Conventional Correlation analysis COVID-19 COVID-19 prognosis creatinine cross database death death prediction model development eosinophil explanation Factor Factor analysis Gradient high mortality rate Hill ICU ICU patient ICU Patients intensive care intensive care unit Interpretation lactate dehydrogenase LIME Logistic regression lymphocyte machine learning machine learning algorithm machine learning model Model Mortality neutrophil objective outcome patients with COVID-19 performed potential risk predict predicted Prognosis prognosis of patient Prothrombin time randomly divided recorded reliability Result risk risk factor risk of death selected SHAP Significance stability total bilirubin training data translated Treatment validation was measured were used with COVID-19 [DOI] 10.2196/23128 PMC 바로가기 [Article Type] Original Paper