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의료분야에서 인공지능 현황 및 의학교육의 방향
Current Status and Future Direction of Artificial Intelligence in Healthcare and Medical Education 원문보기

의학교육논단 = Korean medical education review, v.22 no.2, 2020년, pp.99 - 114  

정진섭 (부산대학교 의과대학 생리학교실)

Abstract AI-Helper 아이콘AI-Helper

The rapid development of artificial intelligence (AI), including deep learning, has led to the development of technologies that may assist in the diagnosis and treatment of diseases, prediction of disease risk and prognosis, health index monitoring, drug development, and healthcare management and ad...

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표/그림 (6)

AI 본문요약
AI-Helper 아이콘 AI-Helper

* AI 자동 식별 결과로 적합하지 않은 문장이 있을 수 있으니, 이용에 유의하시기 바랍니다.

문제 정의

  • 본 종설에서는 인공지능기술의 의료분야 연구개발 현황 및 문제점을 개괄하고 이에 따른 의료의 변화에 대응하는 의학교육의 방향성을 검토해 보고자 한다.
본문요약 정보가 도움이 되었나요?

질의응답

핵심어 질문 논문에서 추출한 답변
인공지능은 옥스퍼드 영어사전에서 어떻게 정의하는가? 인공지능(artificial intelligence)은 옥스퍼드 영어사전에서 “시각 인식, 음성 인식, 의사결정, 언어번역 등 인간의 지능을 필요로 하는 업무를 정상적으로 수행할 수 있는 컴퓨터시스템의 이론과 개발”로 정의하고 있으며[1], 확률적 기계학습(probabilistic machine learning), 진화적 컴퓨팅(evolutionary computing), 전문가시스템(expert system), 퍼지시스템(fuzzy system) 등 다양한 방법을 포함한다. 역사적으로 인공지능 연구는 1943년 McCulloch와 Pitts [2]가 인간 뇌의 신경망을 모식화한 전기회로모델을 제안하였고, 1947년 Alan Turing이 경험을 통해 배우는 기계를 제안하며 시발되었다[2].
심층신경망을 이용한 심층학습기술은 기존 인공지능 기술과 어떤 차이가 있는가? 그러나 토론토 의과대학의 Hinton 교수와 Lecun 교수 연구팀에 의해 오류 역전파(back propagation) [5], 다층신경망 구조[6], 콘볼루션 신경망(convolutional neural network) [7] 등 심층학습의 기본원리가 개발되고 그래픽스 처리장 치(graphic processing unit)를 포함한 하드웨어의 빠른 발전과 빅데이터 확보 등 기반 여건이 성숙됨으로써 도약의 계기를 마련하였다. 2012년 심층신경망을 이용한 심층학습기술이 이미지 인식[8,9]과 음성인식[10]에서 인공지능 분야의 다른 기술보다 현저히 우수한 성능을 보이는 것으로 보고됨에 따라 관련 연구가 폭발적으로 확산 되어 다양한 분야에 적용되었다. 한국에서 인공지능에 대한 큰 대중적 관심을 유도한 사건은 2016년 구글 딥마인드가 개발한 알파고가 프로 바둑의 세계 챔피언인 이세돌을 이기고 바둑에서 일인자가 된 것이었다[11].
인공지능이 의료분야에 적용되어 긍정적 방향으로 활용되기 위해서는 무엇이 필요한가? 이들 기술 중 일부는 규제 당국의 공식 인가를 받아 의료현장에 활용되고 있으며, 이러한 변화가 가속화되면 의료환경의 큰 변화가 예측된다. 그러나 인공지능기술이 의료의 질을 향상시키는 긍정적 방향으로 적용되기 위해서는 인공지능 모델의 개발 환경과 다른 다양한 실제 의료현장에서의 전향적 연구를 통해 훈련 데이터의 편향성, 알고리즘의 투명성을 포함한 알고리즘의 기술적 문제의 유무 판단과 객관적인 효과 검증이 필요하며 나아가 이들 모델이 의료의 질과 환자의 임상적 결과를 개선할 수 있는지도 검토되어야 한다. 또한 인공지능 의료기술의 안전성을 확보하기 위한 규제 및 관리시스템의 정비, 인공지능기술의 확산에 따라 생길 수 있는 윤리적 및 법적 문제, 의사-환자 및 사회관계의 변화 등 다양한 분야에 대한 검토가 필요하다. 이러한 의료환경의 급속한 변화에 능동적으로 적응할 수 있는 의료인력에 대한 체계적인 교육이 필요하다.
질의응답 정보가 도움이 되었나요?

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