An important public health application of ML is the identification and prediction of populations at high risk for developing certain adverse health outcomes and the development of public health interventions targeted to these populations. Various concepts related to ML need to be integrated into the ...
This paper presents a novel machine learning approach to perform an early prediction of the healthcare cost of breast cancer patients. The learning phase of our prediction method considers the following two steps: (1) in the first step, the patients are clustered taking into account the sequence...
a, ROC curve for the crisis prediction task. Comparison among the proposed final model (XGBoost general), a proposed diagnosis-specific model (XGBoost per diagnosis) and two baseline models. The solid lines and lighter-colored envelopes around each line were derived from the test evaluations (n...
Prediction of postpartum hemorrhage (PPH) using machine learning algorithms in a Kenyan population Postpartum hemorrhage (PPH) is a significant cause of maternal mortality worldwide, particularly in low- and middle-income countries. It is essential to de... SY Shah,S Saxena,SP Rani,... - 《...
Disease prediction Using ML to analyze healthcare data and other factors can help in the development of disease prediction models. Such models can better identify risk factors and prevent disease by providing more accurate predictions, which helps in making better decisions about disease cure and prev...
Table 1 Health prediction results using different methods Full size table Finally, we investigated the health prediction performance of hiPCA for 13 different phenotypes. As can be seen from Fig. 2h–k, the health index from PCA showed significant differences in the healthy group compared with tha...
Enhancing Machine Learning Prediction for Pre-Pregnancy Women and Infant Birth Weight Gain in Maternal Healthcare This comprehensive research investigates the utilization of cutting-edge Machine Learning (ML) techniques within the realm of gynecology. To assess the eff... RL Priya,DF Evangil,MGPK Ja...
(3)Liu X,Liu T, Zhang Z, et al. TOP-Net Prediction Model Using Bidirectional Long Short-term Memory and Medical-Grade Wearable Multisensor System for Tachycardia Onset: Algorithm Development Study. JMIR Med Inform. 2021;9(4):e18803. ...
Prediction of the cell-type-specific transcription of non-coding RNAs from genome sequences via machine learning A machine-learning model can reliably link genome sequence and non-coding RNA expression at the cell type level. Masaru Koido
This work provides insights into the design of scalable data-driven models for battery SOH estimation, emphasizing the value of confidence bounds around the prediction. The pipeline methodology combines experimental data with machine learning modelling and could be applied to other critical components ...