{"id":"W3209855943","doi":"10.1145/3465220","title":"Medical Image Classification based on an Adaptive Size Deep Learning Model","year":2021,"lang":"en","type":"article","venue":"ACM Transactions on Multimedia Computing Communications and Applications","topic":"COVID-19 diagnosis using AI","field":"Medicine","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"Brandon University","funders":"Natural Science Foundation of Hainan Province; National Natural Science Foundation of China","keywords":"Deep learning; Artificial intelligence; Computer science; Robustness (evolution); Machine learning; Bilinear interpolation; Contextual image classification; Pattern recognition (psychology); Image (mathematics); Data mining; Computer vision","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":[0.0006445005,0.0005057571,0.0006131364,0.0007301787,0.0002066574,0.0005733909,0.001142961,0.0008978149,0.001461266],"category_scores_gemma":[0.001248606,0.0002844211,0.0007281173,0.0005261598,0.0003911145,0.001088263,0.0007747665,0.0009762383,0.0003897205],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008726715,"about_ca_system_score_gemma":0.0007755303,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005035657,"about_ca_topic_score_gemma":0.005232015,"domain_scores_codex":[0.9997231,0.00003690937,0.00001893109,0.00008157773,0.00009078013,0.00004859202],"domain_scores_gemma":[0.9996928,0.0000866883,0.00003673114,0.00003116564,0.0001302998,0.00002244657],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003561147,0.0002521318,0.00286081,0.00011465,0.0001023692,0.000157829,0.00007799137,0.4972197,0.03229233,0.007670984,0.004717859,0.4541772],"study_design_scores_gemma":[0.000003840767,0.00001951165,0.0001476903,0.000002523689,0.000005772217,0.00001550582,0.000002467293,0.9976005,0.001221357,0.0007687567,0.0002089671,0.000003123964],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0506194,0.0005924945,0.9444495,0.0007691184,0.00009591447,0.00007378887,0.0001446952,0.001101805,0.002153312],"genre_scores_gemma":[0.7913201,0.0006065855,0.1993199,0.0008063204,0.0001197566,0.0001738953,0.0004584491,0.00008018612,0.007114735],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005035657,"threshold_uncertainty_score":0.01001269,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05041496211789009,"score_gpt":0.3529793138213099,"score_spread":0.3025643517034198,"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."}}