{"id":"W4210572355","doi":"10.1002/advs.202104538","title":"Regional Radiomics Similarity Networks Reveal Distinct Subtypes and Abnormality Patterns in Mild Cognitive Impairment","year":2022,"lang":"en","type":"article","venue":"Advanced Science","topic":"Radiomics and Machine Learning in Medical Imaging","field":"Medicine","cited_by":60,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Fundamental Research Funds for the Central Universities; Canadian Institutes of Health Research; National Institutes of Health; H. Lundbeck A/S; Eisai; Servier; Beijing Normal University; Genentech; IXICO; National Natural Science Foundation of China; Pfizer; Novartis Pharmaceuticals Corporation; F. Hoffmann-La Roche; Biogen; Eli Lilly and Company; Bristol-Myers Squibb; BioClinica; U.S. Department of Defense; Alzheimer's Disease Neuroimaging Initiative; Meso Scale Diagnostics; National Institute on Aging; Alzheimer's Association","keywords":"Abnormality; Dementia; Neuroimaging; Cognitive impairment; Cognition; Medicine; Disease; Internal medicine; Bioinformatics; Psychology; Neuroscience; Biology; Psychiatry","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001321686,0.0001104948,0.0002009175,0.000106996,0.0004070072,0.00002344176,0.0001571665,0.00001973638,0.0000353009],"category_scores_gemma":[0.0002512116,0.000103278,0.00003256118,0.0004300128,0.0005124007,0.0001583305,0.0002260879,0.0006288815,4.95112e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002037011,"about_ca_system_score_gemma":0.0001425605,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001065918,"about_ca_topic_score_gemma":0.00001547533,"domain_scores_codex":[0.9984617,0.00007191274,0.0002128992,0.0004298462,0.0004520951,0.0003715685],"domain_scores_gemma":[0.999353,0.0001603383,0.00008285916,0.0001554957,0.00004892132,0.0001993946],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003719742,0.0002080717,0.9652475,0.00004207315,0.000009188581,0.0002150232,0.0006551367,0.004314164,0.0004569412,0.0002806192,0.0001109134,0.02808836],"study_design_scores_gemma":[0.001627822,0.0001668833,0.8686906,0.00008818031,0.00001512235,0.0002461723,0.000382799,0.1280258,0.00003623972,0.0002385283,0.0003379452,0.0001439347],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9927756,0.0003014888,0.004295063,0.001939405,0.0001748879,0.0002687928,0.00001039919,0.00002695071,0.0002074086],"genre_scores_gemma":[0.9969023,0.0000889308,0.000863102,0.001973241,0.00005255481,0.00002938851,0.00002109554,0.000008626924,0.00006079007],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1237116,"threshold_uncertainty_score":0.4211555,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01358018304088768,"score_gpt":0.3013514475775353,"score_spread":0.2877712645366476,"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."}}