최소 단어 이상 선택하여야 합니다.
최대 10 단어까지만 선택 가능합니다.
다음과 같은 기능을 한번의 로그인으로 사용 할 수 있습니다.
NTIS 바로가기한국항행학회논문지 = Journal of advanced navigation technology, v.25 no.1, 2021년, pp.96 - 101
정선우 (전남대학교 ICT융합시스템공학과) , 이민지 (전남대학교 IoT인공지능융합전공) , 유선용 (전남대학교 ICT융합시스템공학과)
This paper presents a machine learning model that predicts stroke risks in atrial fibrillation patients using public big data. As the training data, 68 independent variables including demographic, medical history, health examination were collected from the Korean National Health Insurance Service. T...
* AI 자동 식별 결과로 적합하지 않은 문장이 있을 수 있으니, 이용에 유의하시기 바랍니다.
Global Health Estimates: Life expectancy and leading causes of death and disability [Internet]. Available: https://www.who.int/data/gho/data/themes/mortality-and-global-health-estimates
World Health Organization (2005). WHO STEPS Stroke Manual [Internet]. Available: http://whqlibdoc.who.int/chp/steps/Stroke/en/
Korean Statistical Information Service (KOSIS). Annual Report on the Cause of Death Statistics [Internet]. 2016. Available: https://kosis.kr/eng/search/searchList.do
Stroke Risk in Atrial Fibrillation Working Group, "Independent predictors of stroke in patients with atrial fibrillation: a systematic review," Neurology, Vol. 69, No. 6, pp. 546-554, Aug. 2007.
J. B. Olesen, C. Torp-Pedersen, M. L. Hansen, and G. Y. H. Lip, "The value of the CHA2DS2-VASc score for refining stroke risk stratification in patients with atrial fibrillation with a CHADS2 score 0 - 1: a nationwide cohort study," Thrombosis and Haemostasis, Vol. 107, No. 6, pp. 1172-1179, 2012.
Y. Bengio, A. Courville, and P. Vincent, "Representation learning: A review and new perspectives," IEEE Ttransactions on Pattern Analysis and Machine Intelligence, Vol. 35, No. 8, pp. 1798-1828, Aug. 2013.
J. Schmidhuber, "Deep learning in neural networks: An Overview", Neural Networks, Vol. 61, pp. 85-117, Jan. 2015.
M. M. Lau and K. Hann Lim, "Review of adaptive activation function in deep neural network," in Proceedings of the 2018 IEEE-EMBS Conference on Biomedical Engineering and Sciences (IECBES), Sarawak: Malaysia, pp. 686-690, 2018.
Q. V. Le, J. Ngiam, A. Coates, A. Lahiri, B. Prochnow, and A. Y. Ng, "On optimization methods for deep learning," in Proceedings of the 28th International Conference on Machine Learning, Bellevue: WA, pp. 265-272, Jun. 2011.
D. M. Powers, "Evaluation: from precision, recall and F-measure to ROC, informedness, markedness and correlation," International Journal of Machine Learning Technology, Vol. 2, No. 1, pp. 37-63, 2011.
J. A. Hanley and J. M. Barbara, "The meaning and use of the area under a receiver operating characteristic (ROC) curve," Radiology. Vol. 143, No. 1, pp. 29-36, 1982.
A. P. Bradley, "The use of the area under the ROC curve in the evaluation of machine learning algorithms," Pattern Recognition, Vol. 30, No. 7, pp. 1145-1159, 1997.
J. Keilwagen, I. grosse, and J. Grau, "Area under precision-recall curves for weighted and unweighted data", PloS One, Vol. 9, No. 3, Mar. 2014.
J. Davis, and M. Goadrich., "The relationship between precision-recall and ROC curves.", in Proceedings of the 23rd international conference on Machine learning, New York: NY, pp. 233-240, Jun 2006.
*원문 PDF 파일 및 링크정보가 존재하지 않을 경우 KISTI DDS 시스템에서 제공하는 원문복사서비스를 사용할 수 있습니다.
오픈액세스 학술지에 출판된 논문
※ AI-Helper는 부적절한 답변을 할 수 있습니다.