Scientists aim to create a system that can predict the likelihood of newborns being admitted to the neonatal intensive care unit (NICU) by combining various statistical methods. This prediction could potentially reduce the negative health outcomes, d...
Metabolic Syndrome (MetS) comprises a clustering of conditions that significantly increase the risk of heart disease, stroke, and diabetes. Timely detection and intervention are crucial in preventing severe health outcomes. In this study, we implemen...
Rice planthoppers are the most economically important insect pests of rice in Asia. Traditional surveys to examine their abundance and composition in paddy fields involve human visual inspection, which requires considerable time and effort by expert ...
Large language models (LLMs) can potentially enhance the accessibility and quality of medical information. This study evaluates the reliability and quality of responses generated by ChatGPT-4, an LLM-driven chatbot, compared to those written by physi...
Visceral Leishmaniasis (VL), also known as Kala-Azar, poses a significant global public health challenge and is a neglected disease, with relapses and treatment failures leading to increased morbidity and mortality. This study introduces an explainab...
Occupational data is a crucial social determinant of health, influencing diagnostic accuracy, treatment strategies, and policy-making in healthcare. However, its inclusion in electronic health records (EHR) is often relegated to unstructured fields. ...
Cervical cancer is a major cause of mortality among women, particularly in low-income countries with insufficient screening programs. Manual cytological examination is time-consuming, error-prone and subject to inter-observer variability. Automated a...
Human eye blinks are considered a significant contaminant or artifact in electroencephalogram (EEG), which impacts EEG-based medical or scientific applications. However, eye blink detection can instead be transformed into a potential application of b...
Breast cancer remains a major cause of mortality among women, where early and accurate detection is critical to improving survival rates. This study presents a hybrid classification approach for mammogram analysis by combining handcrafted statistical...
Cancer-associated fibroblasts promote tumor progression through growth facilitation, invasion, and immune evasion. This study investigated the impact of activated cancer-associated fibroblasts (aCAFs) on survival outcomes, immune response, and molecu...
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