{"id":"W4229456659","doi":"10.3390/jpm12050768","title":"A Novel Patient Similarity Network (PSN) Framework Based on Multi-Model Deep Learning for Precision Medicine","year":2022,"lang":"en","type":"article","venue":"Journal of Personalized Medicine","topic":"Machine Learning in Healthcare","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Concordia University","funders":"","keywords":"Computer science; Autoencoder; Deep learning; Artificial intelligence; Convolutional neural network; Encoder; Similarity (geometry); Machine learning; Curse of dimensionality; Word embedding; Feature learning; Embedding; 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":[0.001619409,0.0006937396,0.0009506766,0.001363794,0.0003520288,0.0008643929,0.001322353,0.00123528,0.001725952],"category_scores_gemma":[0.003512655,0.0003083722,0.0008390925,0.001191648,0.0005313876,0.001760786,0.001632973,0.00135724,0.0003568084],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001595487,"about_ca_system_score_gemma":0.001836678,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007055245,"about_ca_topic_score_gemma":0.008538157,"domain_scores_codex":[0.999121,0.0002502653,0.00006464493,0.0002546565,0.0002317315,0.00007756415],"domain_scores_gemma":[0.9992073,0.0003183825,0.0001490628,0.00007062468,0.0001892473,0.0000653844],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002803029,0.0002644029,0.01061196,0.0002129924,0.0002452409,0.0003591932,0.0001613131,0.5018218,0.003039796,0.03264252,0.006851273,0.4435091],"study_design_scores_gemma":[0.00001085111,0.00005584169,0.0006293432,0.00001313882,0.00002409232,0.00008117368,0.00001259295,0.9813151,0.0006801724,0.01594895,0.001218022,0.0000106928],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02342271,0.0008695904,0.9712439,0.001032556,0.0001043018,0.0001355672,0.0006748837,0.0006057198,0.001910818],"genre_scores_gemma":[0.7404064,0.0008596914,0.2518098,0.0008969692,0.0001963003,0.0003457824,0.001757767,0.00006991005,0.003657352],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007055245,"threshold_uncertainty_score":0.01402837,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05258624034517451,"score_gpt":0.350932823783868,"score_spread":0.2983465834386935,"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."}}