Coronary illness is one of the most essential human maladies on the earth and majorly affects human life. With coronary illness, the heart can't drive the necessary measure of blood into different pieces of the body. A precise and opportune analysis of coronary illness is significant for the ...
Quantifying the pathogenicity of protein variants in human disease-related genes would have a marked effect on clinical decisions, yet the overwhelming majority (over 98%) of these variants still have unknown consequences1–3. In principle, computational
Identification of AD (Alzheimer’s disease)-related genes obtained from blood samples is crucial for early AD diagnosis. We used three public datasets, ADNI, AddNeuroMed1 (ANM1), and ANM2, for this study. Five feature selection methods and five classifiers were used to curate AD-related gene...
Social Science Electronic PublishingChaitrali S. Dangare , Sulabha S. Apte , A data mining approach for prediction of heart disease using neural networks. 2012, pp. 30-40.Chaitrali S. Dangare and Dr. Mrs. Sulabha S. Apte, A Data Mining Approach for Prediction of Heart Disease Using ...
Ronghui Xu (East China Normal University, Shanghai), Hanyin Cheng, Chenjuan Guo, Hongfan Gao, Jilin Hu, Sean Bin Yang, Bin Yang. KDD 2025 [link] Efficient Large-Scale Traffic Forecasting with Transformers: A Spatial Data Management Perspective. Yuchen Fang (University of Electronic Science ...
Although they are expensive compared with mass spectrometry-based technologies that capture fewer proteins of higher abundance,5 a large proportion of disease-relevant proteins, such as those involved in signalling or reflecting tissue damage, are expected to be found in the lower end of the ...
Data mining plays a promising and significant role in this aspect. Data Mining techniques can be used for disease prediction. In this research, the classification based data mining techniques are applied to healthcare data. This research focuses on the prediction of heart disease using three ...
The Coronavirus Disease-2019 (COVID-19) pandemic persists to have a mortifying impact on the health and well-being of the global population. A continued ri
In Japan, the prevalence of dementia is expected to reach 4.7 million by 2025. This study aimed to develop a risk score for the prediction of incident dementia in community-dwelling older adults. In this longitudinal observational study, we used data from the Japan Gerontological Evaluation Study...
Predicting the effects of coding variants is a major challenge. While recent deep-learning models have improved variant effect prediction accuracy, they cannot analyze all coding variants due to dependency on close homologs or software limitations. Here