We argue that disease prediction for common multifactorial diseases is greatly improved by considering multiple predisposing genetic and environmental factors concurrently, provided that the model correctly reflects the underlying disease etiology. We show how likelihood ratios can be used to combine ...
Diseases prediction has been performed by machine learning approaches with various biological data. One of the representative data is the gut microbial community, which interacts with the host’s immune system. The abundance of a few microorganisms has b
CNN Prediction of Future Disease Activity for Multiple Sclerosis Patients from Baseline MRI and Lesion LabelsNew T2w and gadolineum-enhancing lesions in Magnetic Resonance Images (MRI) are indicators of new disease activity in Multiple Sclerosis (MS) patients. Predicting future disease activity could ...
Multiple seasonal ARIMA model in prediction of the monthly incidence of the hand-foot-mouth disease 来自 知网 喜欢 0 阅读量: 38 作者:MA Xiao-Mei,Y Liu,ML Yang,GL Yan,XU Xue-Qin,JJ Wang,XI Yuan-Lin,GC Duan 摘要: Objective To explore the value of the multiple seasonal autoregressive ...
Context. The Framingham Heart Study produced sex-specific coronary heart disease (CHD) prediction functions for assessing risk of developing incident CHD
Also, high ICAM-1 expression has been connected to advanced disease and resistance to chemotherapy [41, 42]. Similarly, high CD70 expression has been detected on MM cells and been proposed as a therapeutic target [43]. In concert with these downregulations, an increase in the expression of ...
Most of the vEDGs used to classify MM4 as a tonsil BC–like subtype of disease belonged to a range of gene classes, including adhesion, transcription, signaling, and metabolism, with very few vEDGs being associated with cell proliferation. However, comparison of expression of a panel of proli...
Regarding the sixth-year disease severity prediction, it was also desired to achieve good performance using data from the least number of progression years, the 2-year model was also chosen as the best predictor, reaching an AUC of 0.89 ± 0.03, sensitivity of 0.84 ± 0.11, and specificity ...
The comparison and interaction between the digital twins provide valuable insights (e.g., phenotyping, risk assessment and the prediction of disease evolution) that are clinically interpreted and combined with traditional data to support clinical decision-making. In the process, the digital twin is ...
Consequently, identifying potential disease-related lncRNAs is an effective means to improve the quality of disease diagnostics and treatment, which is the motivation of this work. Here, we propose a computational model (LncDisAP) for potential disease-related lncRNA identification based on multiple ...