{"id":"W4296528405","doi":"10.1111/cns.13963","title":"Machine learning based on Optical Coherence Tomography images as a diagnostic tool for Alzheimer's disease","year":2022,"lang":"en","type":"article","venue":"CNS Neuroscience & Therapeutics","topic":"Retinal Imaging and Analysis","field":"Medicine","cited_by":44,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Natural Science Foundation of China","keywords":"Nerve fiber layer; Retinal; Inner plexiform layer; Optical coherence tomography; Ophthalmology; Medicine; Atrophy; Receiver operating characteristic; Ganglion cell layer; Montreal Cognitive Assessment; Internal medicine; Pathology; Disease; Dementia","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001393133,0.0005022546,0.0004575723,0.00148609,0.000157565,0.0006433878,0.0002951706,0.00048968,0.000668393],"category_scores_gemma":[0.003529288,0.0001013468,0.0003614762,0.0004171704,0.00019572,0.0003938545,0.0002738274,0.0003066302,0.0002307983],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000287343,"about_ca_system_score_gemma":0.0003261415,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00119613,"about_ca_topic_score_gemma":0.001192694,"domain_scores_codex":[0.9995435,0.0002315561,0.0000361236,0.0000778353,0.0000764254,0.00003461881],"domain_scores_gemma":[0.9989271,0.0005899523,0.0002004121,0.00006069149,0.0001723997,0.00004945113],"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":[0.001599582,0.0007442075,0.6388415,0.0001851583,0.0005288905,0.0003406804,0.00008497668,0.03591089,0.008666134,0.0006389397,0.002749563,0.3097095],"study_design_scores_gemma":[0.00006781957,0.0007215546,0.2287126,0.00008634095,0.0002316894,0.0007489069,0.0001029417,0.7614319,0.005054811,0.001552162,0.00125264,0.00003660947],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9552808,0.003075588,0.03804601,0.00058108,0.0001048426,0.0001007802,0.0004564923,0.0003393961,0.002014934],"genre_scores_gemma":[0.9892553,0.000304107,0.009778456,0.00006523547,0.0000455845,0.00003665938,0.0002000497,0.000004083346,0.0003104654],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00148609,"threshold_uncertainty_score":0.00736773,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03460232763328735,"score_gpt":0.3149810567383486,"score_spread":0.2803787291050613,"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."}}