{"id":"W4414811963","doi":"10.1701/4573.45777","title":"Making the case for digital twins: Italian healthcare needs AI-driven predictive modeling for personalized medicine","year":2025,"lang":"en","type":"article","venue":"Recenti Progressi in Medicina","topic":"Engineering Education and Technology","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Interoperability; Precision medicine; Digital health; Health care; Personalized medicine; Personalization; Autonomy; Paradigm shift; Safeguarding","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004764224,0.0001596583,0.000256573,0.0003939807,0.0001800736,0.00006941432,0.0005939535,0.0001214203,0.000002690893],"category_scores_gemma":[0.0005206259,0.0001129932,0.00006057321,0.0008105796,0.0001482705,0.0002090671,0.0001029447,0.0002489737,5.993894e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001501645,"about_ca_system_score_gemma":0.0001761148,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002216351,"about_ca_topic_score_gemma":0.00002104302,"domain_scores_codex":[0.9987558,0.00003291538,0.000347189,0.0003298004,0.0001602664,0.0003740722],"domain_scores_gemma":[0.9989948,0.0002576764,0.00008542585,0.0003953888,0.0002089515,0.00005771163],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001013742,0.0002391951,0.003802826,0.001262703,0.0001637039,0.00009164794,0.01627825,0.001018645,0.00001576458,0.5310212,0.01345276,0.432552],"study_design_scores_gemma":[0.001760848,0.0002865708,0.00004722339,0.001323486,0.00002908452,0.0001532448,0.005818891,0.9441055,0.00001883046,0.01363657,0.03266347,0.000156256],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.006062579,0.003031195,0.8924688,0.09479314,0.001503086,0.001587009,0.00001270886,0.0002799289,0.0002615989],"genre_scores_gemma":[0.9887925,0.00005353054,0.008924223,0.001101624,0.0001686938,0.0007282761,0.00001995337,0.0000152989,0.0001958667],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.98273,"threshold_uncertainty_score":0.460773,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04373821557029269,"score_gpt":0.3689985295816754,"score_spread":0.3252603140113827,"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."}}