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The day when computers read between lines.

Kei Yamada1, Susumu Mori2

  • 1Department of Radiology, Graduate School of Medical Science, Kyoto Prefectural University of Medicine, Kajii-cyo, Kawaramachi Hirokoji Agaru, Kamigyo-ku, Kyoto City, Kyoto, 602-8566, Japan. kyamada@koto.kpu-m.ac.jp.

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PubMed
Summary
This summary is machine-generated.

Artificial general intelligence (AGI) is unlikely to replace physicians due to three key issues: difficulty in establishing medical ground truth, incomplete electronic medical records (EMRs), and the inability to digitize complex human decision-making processes.

Keywords:
Artificial general intelligenceArtificial intelligenceComputer-aided diagnosisElectronic medical recordMRI

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Area of Science:

  • Medical Informatics
  • Artificial Intelligence
  • Healthcare Systems

Background:

  • The increasing capabilities of artificial general intelligence (AGI) raise questions about its potential to automate tasks currently performed by healthcare professionals.
  • Concerns exist regarding the feasibility of AGI replacing physicians in clinical practice.

Purpose of the Study:

  • To identify and discuss significant barriers preventing artificial general intelligence (AGI) from replacing physicians.
  • To critically evaluate the limitations of current AI in the context of medical practice.

Main Methods:

  • Analysis of the challenges in obtaining definitive ground truth for medical conditions.
  • Evaluation of the completeness and utility of electronic medical record (EMR) data for AGI development.
  • Exploration of the inherent difficulties in quantifying and digitizing complex human cognitive processes in medical decision-making.

Main Results:

  • Establishing definitive ground truth for a majority of medical conditions presents a significant challenge.
  • Electronic medical records (EMRs) capture only a fraction of the data essential for comprehensive patient care, limiting their suitability for AGI training.
  • Crucial aspects of clinical decision-making, including intuition and nuanced judgment, cannot be effectively translated into computable formats.

Conclusions:

  • The inherent complexities of medical data and decision-making pose substantial obstacles to the development of AGI capable of replacing physicians.
  • Current limitations in data availability and the nature of clinical reasoning suggest that AGI will augment, rather than replace, human medical expertise in the foreseeable future.