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Time Series Prediction Using Deep Learning Methods in Healthcare
2022
ACM Transactions on Management Information Systems
Traditional Machine Learning (ML) methods face unique challenges when applied to healthcare predictive analytics. The high-dimensional nature of healthcare data necessitates labor-intensive and time-consuming processes when selecting an appropriate set of features for each new task. Furthermore, ML methods depend heavily on feature engineering to capture the sequential nature of patient data, oftentimes failing to adequately leverage the temporal patterns of medical events and their
doi:10.1145/3531326
fatcat:w2mml2pc2fdnpazjkpi2hqpvgq