The effect of an artificial intelligence algorithm on chest X-ray interpretation of radiology residents.

Journal: The British journal of radiology
Published Date: Oct 5, 2022

Abstract

OBJECTIVE: Chest X-rays are the most commonly performed diagnostic examinations. An artificial intelligence (AI) system that evaluates the images fast and accurately help reducing workflow and management of the patients. An automated assistant may reduce the time of interpretation in daily practice. We aim to investigate whether radiology residents consider the recommendations of an AI system for their final decisions, and to assess the diagnostic performances of the residents and the AI system.

Authors

  • Yeliz Pekçevik
    Health Sciences University, Tepecik Training and Research Hospital, Department of Radiology, Izmir, Turkey.
  • Dilek Orbatu
    Health Sciences University, Tepecik Training and Research Hospital, Department of Child Health and Diseases, Izmir, Turkey.
  • Fatih Güngör
    Faculty of Medicine, Dokuz Eylül University, Izmir, Turkey.
  • Oktay Yıldırım
    Faculty of Engineering, Department of Computer Engineering, Dokuz Eylül University, Izmir, Turkey.
  • Eminullah Yaşar
    Faculty of Engineering, Department of Computer Engineering, Dokuz Eylül University, Izmir, Turkey.
  • Mohammed Abebe Yimer
    Faculty of Engineering, Department of Computer Engineering, Dokuz Eylül University, Izmir, Turkey.
  • Ali Rıza Şişman
    Faculty of Medicine, Department of Medical Biochemistry, Dokuz Eylül University, Izmir, Turkey.
  • Mustafa Emiroğlu
    Health Sciences University, Tepecik Training and Research Hospital, Department of General Surgery, Izmir, Turkey.
  • Lan Dao
    Quebec Artificial Intelligence Institute, Department of Medicine, University of Montreal, Mila, Quebec, Canada.
  • Joseph Paul Cohen
    Unity Health Toronto (Verma, Murray, Straus, Pou-Prom, Mamdani); Li Ka Shing Knowledge Institute of St. Michael's Hospital (Verma, Straus, Pou-Prom, Mamdani); Department of Medicine (Verma, Shojania, Straus, Mamdani) and Institute of Health Policy, Management, and Evaluation (Verma, Mamdani) and Department of Statistics (Murray), University of Toronto, Toronto, Ont.; University of Alberta (Greiner); Alberta Machine Intelligence Institute (Greiner), Edmonton, Alta.; Montreal Institute for Learning Algorithms (Cohen), Montréal, Que.; Centre for Quality Improvement and Patient Safety (Shojania), University of Toronto; Sunnybrook Health Sciences Centre (Shojania); Vector Institute (Ghassemi, Mamdani) and Department of Computer Science (Ghassemi); Leslie Dan Faculty of Pharmacy (Mamdani), University of Toronto, Toronto, Ont.; Department of Radiology, Stanford University (Cohen), Stanford, Calif.
  • Suleyman Sevinc
    Department of Computer Engineering, Faculty of Engineering, Dokuz Eylül University, Izmir, Turkey.

Keywords

External Resources

Popular Topics
Recent Journals