Development of Machine-learning Model to Predict Anticoagulant Use and Type in Geriatric Traumatic Brain Injury Using Coagulation Parameters - ONUKI, Takahiro; OKADA, Yohei; HAJI, Kohei; FUJIWARA, Gaku; HIROTA, Shin; SHIOMI, Naoto; MAEDA, Takeshi; INAJI, Motoki; YATSUSHIGE, Hiroshi; MIYATA, Akihiro; KOMORIBAYASHI, Nobukazu; KARIBE, Hiroshi; et al. (Neurologia Medico-Chirurgica, 2025)
Keywords: Aged; Aged, 80 and over; anticoagulant therapy; Anticoagulants; Anticoagulants - therapeutic use; Brain Injuries, Traumatic - blood; Brain Injuries, Traumatic - complications; Brain Injuries, Traumatic - drug therapy; Coagulation; direct oral anticoagulants; Female; Geriatrics; Humans; International Normalized Ratio; Japan; Learning algorithms; Machine Learning; Male; Original; Partial Thromboplastin Time; Prediction models; Prothrombin; Retrospective Studies; Thromboplastin; Trauma; Traumatic brain injury; Vitamin K; Vitamin K - antagonists & inhibitors; vitamin K antagonist; Japan; traumatic brain injury; direct oral anticoagulants; machine learning; vitamin K antagonist; anticoagulant therapy