{"id":"W4393281598","doi":"10.1097/js9.0000000000001371","title":"A real-time augmented reality system integrated with artificial intelligence for skin tumor surgery: experimental study and case series","year":2024,"lang":"en","type":"article","venue":"International Journal of Surgery","topic":"Cutaneous Melanoma Detection and Management","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada); SKiN Health","funders":"National Key Research and Development Program of China; Ministry of Industry and Information Technology of the People's Republic of China; China Postdoctoral Science Foundation; Tencent","keywords":"Medicine; Augmented reality; Sampling (signal processing); Navigation system; Surgical margin; Surgical planning; Surgery; Segmentation; Artificial intelligence; Computer vision; Computer science; Resection","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":[0.0009086408,0.001196808,0.0007804969,0.001012206,0.000742678,0.0007759103,0.0008033369,0.001804505,0.002325341],"category_scores_gemma":[0.001725431,0.0005515613,0.001286189,0.0006457702,0.001565041,0.0007066255,0.0009865927,0.00121039,0.001114888],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004420513,"about_ca_system_score_gemma":0.0006391719,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006206488,"about_ca_topic_score_gemma":0.0009606705,"domain_scores_codex":[0.9988626,0.0002886828,0.0001861348,0.0001755105,0.0002956149,0.0001914821],"domain_scores_gemma":[0.9991471,0.0002429248,0.0001545499,0.0002460194,0.00006557879,0.0001438127],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"case_report","study_design_gemma":"observational","study_design_scores_codex":[0.003768707,0.02006987,0.08220753,0.001810482,0.0007701723,0.4813286,0.004667426,0.006404377,0.1927675,0.001351143,0.002539328,0.2023149],"study_design_scores_gemma":[0.0007194975,0.04159344,0.06443954,0.0001959846,0.0005819338,0.7702857,0.002245901,0.0211145,0.08869722,0.0006373319,0.009178621,0.0003104288],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9821222,0.001208108,0.01463669,0.0001733749,0.0001047563,0.0003316834,0.00008955722,0.0001117964,0.001221799],"genre_scores_gemma":[0.9887834,0.0009361941,0.008666771,0.0001378596,0.00006123041,0.0001597011,0.00009311482,0.00002341503,0.001138314],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002325341,"threshold_uncertainty_score":0.007779002,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0476015840296385,"score_gpt":0.317827096729713,"score_spread":0.2702255127000746,"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."}}