2023 Fiscal Year Final Research Report

Development of algorithm for predicting risk of pulmonary complications after cardiac surgery using artificial intelligence rule extraction technology

Research Project

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Project/Area Number	21K09084
Research Category	Grant-in-Aid for Scientific Research (C)
Allocation Type	Multi-year Fund
Section	一般
Review Section	Basic Section 55060:Emergency medicine-related
Research Institution	Tokyo Women's Medical University
Principal Investigator	Ichiba.shingo Shingo 東京女子医科大学, 医学部, 教授 (30284102)
Co-Investigator(Kenkyū-buntansha)	野村岳志東京女子医科大学, 医学部, 教授 (10243445) 林陽一明治大学, 理工学部, 専任教授 (20189666) 新浪博東京女子医科大学, 医学部, 教授 (30241079) 佐藤暢夫聖マリアンナ医科大学, 医学部, 准教授 (80439869) 清野雄介東京女子医科大学, 医学部, 准講師 (90366352)
Project Period (FY)	2021-04-01 – 2024-03-31
Keywords	人工知能 / 集中治療 / 心臓外科 / アルゴリズム
Outline of Final Research Achievements	Cardiovascular surgery is one of the most invasive surgical procedures requiring ICU admission and, depending on complications, long-term ICU management. A particular risk factor for prolonged ICU stay is the model of pulmonary complications. We hypothesized that early discharge from the ICU would be possible if the risk of these prolonged complications could be estimated in advance. In this study, we investigated the feasibility of creating an algorithm for postoperative complications of cardiovascular surgery using artificial intelligence.
Free Research Field	生体工学
Academic Significance and Societal Importance of the Research Achievements	心臓血管外科のICU長期化リスクを事前に予知することで、真のハイリスク症例を自動で検出するだけでにとどまらず、本研究を実施することでICU入室患者総数を大きく減らすことが可能となり、医師のタスクシフトが可能になると考えた。その結果、1泊10万円を超えるICU入室にかかる社会的負担を減らすことが可能となる。