The world has a higher count of death rates as a result of Alcohol consumption. Identification is possible because Alcoholic EEG waves have a certain behavior that is totally different compared to the non-alcoholic individual. The available approache...
Cancer stem cells (CSCs) have the potential to self-renew and induce cancer, which may contribute to a poor prognosis by enabling metastasis, recurrence, and therapy resistance. Hence, this study was performed to identify the association between CSC-...
The challenge of sustaining user engagement in eHealth interventions is a pressing issue with significant implications for the effectiveness of these digital health tools. This study investigates user engagement in a cognitive-behavioral therapy-base...
In the field of spinal pathology, sagittal balance of the spine is usually judged by the spatial structure and morphology of pelvis, which can be represented by pelvic parameters. Pelvic parameters, including pelvic incidence, pelvic tilt and sacral ...
Diabetic retinopathy (DR), a leading cause of blindness in diabetic patients, necessitates the precise segmentation of lesions for the effective grading of lesions. DR multi-lesion segmentation faces the main concerns as follows. On the one hand, ret...
This study investigated whether machine learning (ML) has better predictive accuracy than logistic regression analysis (LR) for gait independence at discharge in subacute stroke patients (nā=ā843) who could not walk independently at admission. We dev...
Single-cell RNA sequencing (scRNA-seq) has emerged as a pivotal tool for exploring cellular landscapes across diverse species and tissues. Precise annotation of cell types is essential for understanding these landscapes, relying heavily on empirical ...
Non-alcoholic Fatty Liver Disease (NAFLD), noted for its widespread prevalence among adults, has become the leading chronic liver condition globally. Simultaneously, the annual disease burden, particularly liver cirrhosis caused by NAFLD, has increas...
Alzheimer's disease (AD), the most prevalent form of dementia, requires early prediction for timely intervention. Current deep learning approaches, particularly those using traditional neural networks, face challenges such as handling high-dimensiona...
Predicting the spread trends of a pandemic is crucial, but long-term prediction remains challenging due to complex relationships among disease spread stages and preventive policies. To address this issue, we propose a novel approach that utilizes dat...
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