{"id":"W4281994448","doi":"10.1016/j.nicl.2022.103065","title":"Role of artificial intelligence in MS clinical practice","year":2022,"lang":"en","type":"review","venue":"NeuroImage Clinical","topic":"Multiple Sclerosis Research Studies","field":"Medicine","cited_by":71,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Bristol-Myers Squibb Canada; Biogen; Bayer","keywords":"Computer science; Artificial intelligence; Clinical Practice; Machine learning; Field (mathematics); Segmentation; Software; Multiple sclerosis; Deep learning; Applications of artificial intelligence; Data science; Medicine","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002848541,0.0008527223,0.001830185,0.003244156,0.000332486,0.002510258,0.001009522,0.002366373,0.002888083],"category_scores_gemma":[0.005903945,0.0003264081,0.000794791,0.002724551,0.001322832,0.002145462,0.001184474,0.003160248,0.001097273],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001549446,"about_ca_system_score_gemma":0.00284066,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001661276,"about_ca_topic_score_gemma":0.001966254,"domain_scores_codex":[0.9986271,0.0005545269,0.0002397103,0.0001443598,0.0003775995,0.00005673711],"domain_scores_gemma":[0.9946482,0.004291832,0.0003012317,0.00009609883,0.0005546109,0.000108057],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003889405,0.00003772402,0.0001947262,0.02613051,0.0001532789,0.00008919764,0.0001268631,0.0003542254,0.0001589327,0.008906135,0.0156681,0.9481414],"study_design_scores_gemma":[0.00003213945,0.0001035372,0.001751201,0.04382898,0.0002735315,0.0009333266,0.0001760914,0.0003400839,0.0002559285,0.01356978,0.9386889,0.00004637302],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00004548291,0.998322,0.0001076104,0.0008246199,0.0001392632,0.00000335499,0.000005758246,0.000004448075,0.000547606],"genre_scores_gemma":[0.0009313997,0.9979833,0.000264825,0.0004517843,0.0002227896,0.000009751639,0.00001025337,0.000001844899,0.000123958],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.003244156,"threshold_uncertainty_score":0.01506466,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4943063605477632,"score_gpt":0.5810902560821286,"score_spread":0.08678389553436539,"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."}}