{"id":"W4378516263","doi":"10.3390/diagnostics13101691","title":"Prediction of Cognitive Decline in Parkinson’s Disease Using Clinical and DAT SPECT Imaging Features, and Hybrid Machine Learning Systems","year":2023,"lang":"en","type":"article","venue":"Diagnostics","topic":"Parkinson's Disease Mechanisms and Treatments","field":"Medicine","cited_by":90,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Cross-validation; Artificial intelligence; Analysis of variance; Feature selection; Pattern recognition (psychology); Classifier (UML); Montreal Cognitive Assessment; Perceptron; Machine learning; Computer science; Medicine; Cognitive impairment; Artificial neural network; Disease; Pathology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003263915,0.0001501618,0.0003341444,0.0001713062,0.00006539835,0.00002525877,0.00002635291,0.0000319673,0.000004332945],"category_scores_gemma":[0.001920876,0.0001364676,0.00004379851,0.0001632158,0.00009236598,0.00006382727,0.0001002395,0.0001924631,0.000002949886],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002811078,"about_ca_system_score_gemma":0.00005944659,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001997809,"about_ca_topic_score_gemma":0.00001413765,"domain_scores_codex":[0.9988406,0.0001092511,0.000324256,0.0003256415,0.0002019308,0.0001983513],"domain_scores_gemma":[0.9986917,0.0007770772,0.0001078337,0.0001095556,0.00005560162,0.0002581718],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002728495,0.0002146117,0.9939553,0.0001437078,0.00006621514,0.001707074,0.00004732333,0.00004024637,0.00002147204,0.00002651982,0.00009754508,0.003407163],"study_design_scores_gemma":[0.003141804,0.0001277419,0.9215041,0.0009335085,0.0004415229,0.00008177255,0.0001401635,0.07240067,0.00004808543,0.00008412562,0.00100839,0.00008805127],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.99061,0.007596691,0.000189715,0.0001034038,0.0002206076,0.0004255508,0.0007644973,0.00005829617,0.00003125348],"genre_scores_gemma":[0.9904857,0.008543154,0.0001004331,0.00007320954,0.0001264175,0.0000165331,0.0006025954,0.00002611659,0.00002580885],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07245111,"threshold_uncertainty_score":0.5564987,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04029298333189456,"score_gpt":0.3200362706805601,"score_spread":0.2797432873486655,"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."}}