{"id":"W4404494219","doi":"10.1145/3674658.3674687","title":"Assessing Patient Eligibility for Inspire Therapy through Machine Learning and Deep Learning Models","year":2024,"lang":"en","type":"article","venue":"","topic":"Machine Learning in Healthcare","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Computer science; Deep learning; Artificial intelligence; Machine learning","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":[0.00111343,0.0002824353,0.0006250077,0.0006340905,0.0003167626,0.0007828745,0.0003434715,0.001018642,0.004359337],"category_scores_gemma":[0.009024048,0.00008635048,0.0005426932,0.0003578404,0.0001834398,0.0007786052,0.0005509356,0.0009842982,0.0009714729],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004101856,"about_ca_system_score_gemma":0.0009495775,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002359824,"about_ca_topic_score_gemma":0.005528772,"domain_scores_codex":[0.9994821,0.0001718453,0.00007574244,0.00007158025,0.0001283146,0.00007042635],"domain_scores_gemma":[0.9957649,0.002358411,0.0006918241,0.0001469967,0.0006002687,0.0004376883],"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":[0.003353322,0.001168163,0.7804486,0.0001408068,0.0001615041,0.0003544527,0.0001453207,0.01350702,0.002655418,0.001382304,0.006035577,0.1906475],"study_design_scores_gemma":[0.0003025585,0.003961411,0.7101357,0.0003913061,0.0004021404,0.001342187,0.0007495145,0.2554561,0.007695022,0.008386792,0.01105649,0.0001207474],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9705352,0.001253467,0.01188552,0.003324509,0.00008426928,0.0001204598,0.001901386,0.00020599,0.01068932],"genre_scores_gemma":[0.990858,0.0003703281,0.0054844,0.0003034035,0.00003091816,0.00006101099,0.001172184,0.00001987024,0.001699742],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004359337,"threshold_uncertainty_score":0.01458341,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06677967952671057,"score_gpt":0.3761381871395605,"score_spread":0.30935850761285,"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."}}