{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001265778,0.0008008239,0.0005646675,0.001675966,0.0001846817,0.0006365469,0.0003462331,0.0005051763,0.0005674439],"category_scores_gemma":[0.002066932,0.000151837,0.0006228891,0.0005239384,0.0002160852,0.0004130071,0.000509279,0.0003632717,0.0001961017],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004889153,"about_ca_system_score_gemma":0.0003745597,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003100076,"about_ca_topic_score_gemma":0.003764042,"domain_scores_codex":[0.9996669,0.00008553571,0.00003631973,0.00009780958,0.00006142959,0.00005195906],"domain_scores_gemma":[0.999292,0.0003194716,0.0001015715,0.0000530437,0.0001650247,0.0000688375],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001962774,0.0007921339,0.6051691,0.0001398691,0.0008507186,0.0002750414,0.0001247134,0.1091394,0.008778016,0.0001598378,0.001171228,0.2714371],"study_design_scores_gemma":[0.00007040011,0.001405553,0.2632582,0.00005135564,0.0003000347,0.0003869589,0.0001167354,0.7273871,0.005839643,0.0006383199,0.0004988011,0.00004684049],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9891279,0.0005071107,0.009224965,0.0000812558,0.00001848624,0.00003274207,0.000393615,0.0001449162,0.000468901],"genre_scores_gemma":[0.9961821,0.0000546849,0.003227728,0.00001692436,0.00001260613,0.00002068879,0.0003335727,0.000002950762,0.0001486504],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003100076,"threshold_uncertainty_score":0.006694138,"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."}}