{"id":"W4321016468","doi":"10.1155/2023/4301745","title":"Detection of COVID‐19 Case from Chest CT Images Using Deformable Deep Convolutional Neural Network","year":2023,"lang":"en","type":"article","venue":"Journal of Healthcare Engineering","topic":"COVID-19 diagnosis using AI","field":"Medicine","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lakehead University","funders":"Khulna University; King Saud University","keywords":"Convolutional neural network; Artificial intelligence; Deep learning; Computer science; Coronavirus disease 2019 (COVID-19); Pattern recognition (psychology); Image registration; Machine learning; Infectious disease (medical specialty); Pathology; Medicine; Image (mathematics); Disease","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003655379,0.0009419997,0.0004315875,0.001373819,0.0001998911,0.0004659327,0.0007847878,0.0007303773,0.001449265],"category_scores_gemma":[0.0008513733,0.0003258658,0.0006416732,0.0003649133,0.000226856,0.0005221556,0.0005141407,0.000433587,0.0004664922],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006209337,"about_ca_system_score_gemma":0.0005899551,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0110304,"about_ca_topic_score_gemma":0.01393596,"domain_scores_codex":[0.9997426,0.00002469717,0.00002054426,0.0000733958,0.0000863618,0.00005239831],"domain_scores_gemma":[0.9998216,0.00003869956,0.000024915,0.00002333275,0.0000686179,0.00002287709],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007088539,0.0004942872,0.02894258,0.0002445063,0.0002683078,0.001877143,0.000108732,0.2126085,0.08860511,0.00107164,0.008533776,0.6565366],"study_design_scores_gemma":[0.000009209857,0.00008911067,0.005960546,0.00001669776,0.00004144608,0.0002826206,0.00002201403,0.9778292,0.0144575,0.0003690005,0.0009028803,0.0000196147],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5528647,0.002567416,0.4285601,0.0008820411,0.0003560537,0.0002977439,0.001517892,0.005263837,0.007690188],"genre_scores_gemma":[0.8949515,0.001156575,0.09537423,0.0003246117,0.00006636223,0.00009516237,0.002414163,0.00008741163,0.005530139],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0110304,"threshold_uncertainty_score":0.02193242,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0427888264543686,"score_gpt":0.3306680465819815,"score_spread":0.2878792201276129,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}