{"id":"W4402525156","doi":"10.1049/pbhe060e_ch12","title":"Importance and need of IoMT and big data to revolutionizing healthcare industry","year":2024,"lang":"en","type":"book-chapter","venue":"","topic":"Smart Systems and Machine Learning","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Impact","funders":"","keywords":"Healthcare industry; Health care; Big data; Business; Internet privacy; Computer science; Data science; Economics; Data mining","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":[0.002362191,0.0005071251,0.0004002677,0.001081326,0.001175141,0.006065143,0.000744292,0.001503276,0.003813679],"category_scores_gemma":[0.004016129,0.0003336616,0.0005218103,0.001898243,0.002017118,0.00767322,0.002227329,0.004231322,0.001745602],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001668319,"about_ca_system_score_gemma":0.004223442,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001226807,"about_ca_topic_score_gemma":0.001657009,"domain_scores_codex":[0.9981163,0.0004923624,0.00009410815,0.000159341,0.0009307666,0.0002071546],"domain_scores_gemma":[0.9967875,0.001678556,0.0001654554,0.00020194,0.0007758107,0.0003907101],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00005118633,0.00008528732,0.001302178,0.001929808,0.00003064557,0.0003406974,0.002539076,0.001522801,0.00314057,0.4276163,0.1846871,0.3767543],"study_design_scores_gemma":[0.000002770925,0.00003380378,0.0005605254,0.001271993,0.00001273483,0.0002330929,0.001038937,0.001214307,0.000997137,0.05878944,0.9358214,0.00002403557],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"other","genre_scores_codex":[0.01056457,0.3139545,0.1006195,0.3162233,0.02332496,0.0003984052,0.0005108261,0.00105408,0.2333499],"genre_scores_gemma":[0.09360313,0.6539802,0.1237764,0.03805865,0.01656006,0.0003330556,0.0008279912,0.0004897631,0.07237067],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.006065143,"threshold_uncertainty_score":0.01275802,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09219344926329523,"score_gpt":0.2933225801406872,"score_spread":0.201129130877392,"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."}}