Identification of skills in chest XP image diagnoses based on reverser inferences approach

2023 Fiscal Year Final Research Report

• Project/Area Number: 21K04528
• Research Category: Grant-in-Aid for Scientific Research (C)
• Allocation Type: Multi-year Fund
• Section: 一般
• Review Section: Basic Section 25010:Social systems engineering-related
• Research Institution: Tokyo Institute of Technology
• Principal Investigator: Aoki Hirotaka 東京工業大学, 工学院, 准教授 (00322090)
• Co-Investigator(Kenkyū-buntansha): 森下 幸治 東京医科歯科大学, 医学部附属病院, 講師 (40456207)
• Project Period (FY): 2021-04-01 – 2024-03-31
• Keywords: 眼球運動解析 / 技能解析 / XP画像診断

Outline of Final Research Achievements

The present study aimed at developing the reverse inference approach to interpret eye tracking data during performing cognitive tasks, and implementing it to the analysis of skills in diagnosing chest XP images by medical doctors. In the study, the doctors’ strategy for effective diagnoses as well as their corresponding eye movement patterns were systematically identified. Based on the data analysis, the knowledge of well-skilled doctors’ strategies, and their differences from those held by doctors having different background and residents could be obtained.

Free Research Field

認知人間工学

Academic Significance and Societal Importance of the Research Achievements

一般に実施が困難な認知作業分析を，扱いが困難な眼球運動データを効率的に解釈していく手順を準備することによって，専門的知識を有さない人でも実施が可能なアプローチ方法を提供することができた．さらにこれを医師の胸部XP画像診断を対象とした分析に適用することで，高度な技能に関する知見を得ることができた．