{"id":"W7119965719","doi":"10.1002/alz70856_107784","title":"Predicting Alzheimer's Disease Assessment Scale from T1‐weighted MRIs by Fine‐tuning a Pretrained Deep Learning Model","year":2025,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Dementia and Cognitive Impairment Research","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"","keywords":"Deep learning; Robustness (evolution); Scale (ratio); Training set; Test data; Artificial neural network","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":[0.001493634,0.001466919,0.0007211971,0.0006450428,0.0003002509,0.000503026,0.00113568,0.001002368,0.001031963],"category_scores_gemma":[0.003092713,0.0004776471,0.001158197,0.0003537393,0.0003624009,0.0007237842,0.0007102695,0.002207139,0.0006282949],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008990699,"about_ca_system_score_gemma":0.00118138,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01248025,"about_ca_topic_score_gemma":0.01680261,"domain_scores_codex":[0.9996934,0.00004694717,0.00002148743,0.0001461043,0.00003776069,0.00005439972],"domain_scores_gemma":[0.9992197,0.0003269987,0.00007958688,0.00009233235,0.0002308653,0.00005053811],"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":[0.0003080421,0.0003992702,0.02400405,0.00008047746,0.0002382793,0.0002002858,0.00008945416,0.8060337,0.01173649,0.0005468036,0.007300695,0.1490625],"study_design_scores_gemma":[0.0000102569,0.00005586058,0.002081096,0.00001199724,0.00003382214,0.00003179694,0.000006184226,0.994809,0.001959421,0.0006133321,0.0003761141,0.00001101467],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6271559,0.001643786,0.3596731,0.001069402,0.0003395976,0.0001918077,0.00184932,0.005130191,0.002946957],"genre_scores_gemma":[0.914194,0.0003653694,0.07885692,0.0004944305,0.00008517665,0.0002084432,0.002922101,0.000130502,0.002742957],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01248025,"threshold_uncertainty_score":0.0248152,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01704009531703425,"score_gpt":0.3095621957454423,"score_spread":0.292522100428408,"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."}}