{"id":"W4307357561","doi":"10.1101/2022.10.21.513161","title":"PiDeeL: Pathway-Informed Deep Learning Model for Survival Analysis and Pathological Classification of Gliomas","year":2022,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Radiomics and Machine Learning in Medical Imaging","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Bilim Akademisi; Centre National de la Recherche Scientifique","keywords":"Computer science; Artificial intelligence; Deep learning; Concordance; Machine learning; Recall; Pathological; Data mining; Medicine; Pathology; Internal medicine; Psychology; Cognitive psychology","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001761579,0.0004222977,0.001171782,0.0007133698,0.0002384699,0.00007579033,0.0002925506,0.0004044567,0.00004860143],"category_scores_gemma":[0.002318298,0.0004107109,0.0004108996,0.0008224518,0.0002179474,0.00007488953,0.0004294353,0.001415007,0.000001257398],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002306899,"about_ca_system_score_gemma":0.0005172105,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002932347,"about_ca_topic_score_gemma":0.000002444076,"domain_scores_codex":[0.9970463,0.0001879293,0.0008240566,0.0008986986,0.000579849,0.0004631998],"domain_scores_gemma":[0.9974235,0.0003349573,0.0007365521,0.0007520309,0.0004218299,0.0003311357],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005775687,0.0005359623,0.3751108,0.003040356,0.002597733,0.0001196691,0.0002192981,0.02652769,0.5864634,0.004451887,0.00006835838,0.0002872896],"study_design_scores_gemma":[0.0009872153,0.0001457633,0.2770154,0.0001023962,0.00137372,6.188544e-8,0.00002460243,0.7168559,0.002234723,0.000009368039,0.0008562834,0.0003944575],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8142949,0.0005770907,0.1833814,0.0004040101,0.0002708843,0.0007382791,0.00008779478,0.0002197124,0.00002596683],"genre_scores_gemma":[0.9677673,0.0003648666,0.03117813,0.0001279722,0.0001649579,0.0002799092,0.000008865743,0.00009017294,0.00001780707],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6903282,"threshold_uncertainty_score":0.9998345,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02614470159240709,"score_gpt":0.2810491576193161,"score_spread":0.254904456026909,"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."}}