정보처리학회 논문지 (The Transactions of the Korea Information Processing Society)

한국정보처리학회 (Korea Information Processing Society)
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신경망 내 잔여 블록을 활용한 콕스 모델 개선: 자궁경부암 사망률 예측모형 연구

Cox Model Improvement Using Residual Blocks in Neural Networks: A Study on the Predictive Model of Cervical Cancer Mortality

  • 이낭경 (성균관대학교 소프트웨어학과 ) ;
  • 김주영 (국립암센터 방사선종양학과/국립암센터 국제암대학원대학교) ;
  • 탁지수 (성균관대학교 메타바이오헬스학과 ) ;
  • 이형록 (인제대학교 통계학과 ) ;
  • 전현지 (성균관대학교 메타바이오헬스학과) ;
  • 양지명 (서울아산병원 안과 ) ;
  • 이승원 (성균관대학교 의학대학)
  • Nang Kyeong Lee ;
  • Joo Young Kim ;
  • Ji Soo Tak ;
  • Hyeong Rok Lee ;
  • Hyun Ji Jeon ;
  • Jee Myung Yang ;
  • Seung Won Lee
  • 투고 : 2024.03.22
  • 심사 : 2024.05.07
  • 발행 : 2024.06.30
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초록

자궁경부암은 전 세계적으로 여성에게 발생하는 암 중 네 번째로 흔한 암이며, 2020년 한 해 동안 60만 4천 건 이상의 신규 케이스가 보고되었고 이로 인한 사망자 수는 약 34만 1천 831명에 달했다. 콕스 회귀 모델은 암 연구에서 널리 채택되고 있는 주요 모델이지만, 비선형 연관성의 존재를 고려하면 선형 가정으로 인해 한계에 부딪힌다. 이러한 문제를 해결하기 위해, 본 논문에서는 ResNet의 잔여 학습 프레임워크를 활용하여 자궁경부암 사망률 예측의 정확성을 개선한 새로운 모델인 ResSurvNet을 제안한다. 이 모델은 본 연구에서 비교한 DNN, CPH, CoxLasso, Cox Gradient Boost, RSF 모델들을 능가하는 정확도를 보여주었기에 이러한 우수한 예측 성능은 자궁경부암 환자 관리에 있어 조기 진단 및 치료 전략 수립에 기여할 수 있고 임상적으로 적용할 때 큰 가치가 있음을 입증하며, 생존 분석 분야에서도 의미 있는 진전을 나타낸다.

Cervical cancer is the fourth most common cancer in women worldwide, and more than 604,000 new cases were reported in 2020 alone, resulting in approximately 341,831 deaths. The Cox regression model is a major model widely adopted in cancer research, but considering the existence of nonlinear associations, it faces limitations due to linear assumptions. To address this problem, this paper proposes ResSurvNet, a new model that improves the accuracy of cervical cancer mortality prediction using ResNet's residual learning framework. This model showed accuracy that outperforms the DNN, CPH, CoxLasso, Cox Gradient Boost, and RSF models compared in this study. As this model showed accuracy that outperformed the DNN, CPH, CoxLasso, Cox Gradient Boost, and RSF models compared in this study, this excellent predictive performance demonstrates great value in early diagnosis and treatment strategy establishment in the management of cervical cancer patients and represents significant progress in the field of survival analysis.

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과제정보

이 논문은 대한암연구재단 암연구지원사업 연구비(2년)에 의하여 연구되었음(CB-2020-B-2).

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