Skin diseases are an important global public health issue, causing significant health and psychological burdens. Predicting dermatology outpatient visits is essential for optimizing hospital resources and improving diagnosis and treatment methods. Ba...
Arrhythmias are common and can affect individuals with or without structural heart disease. Deep learning models (DLMs) have shown the ability to recognize arrhythmias using 12-lead electrocardiograms (ECGs). However, the limited types of arrhythmias...
We examine how artificial intelligence (AI) integration in healthcare may create an "efficiency paradox" where technologies designed to reduce workload can instead generate new layers of inefficiency. We argue that AI implementation strategies priori...
Drug response prediction (DRP) is a central task in the era of precision medicine. Over the past decade, the emergence of deep learning (DL) has greatly contributed to addressing DRP challenges. Notably, the prediction of DRP for cancer cell lines be...
The increasing availability of wearable device data provides an opportunity for developing personalized models for health monitoring and condition prediction. Unlike conventional approaches that rely on pooled data from diverse individuals, our study...
BACKGROUND: Artificial intelligence (AI) chatbots are increasingly used for medical inquiries, including sensitive topics like sexually transmitted diseases (STDs). However, concerns remain regarding the reliability and readability of the information...
Breast cancer classification using gene expression data presents significant challenges due to high dimensionality and complexity. This study introduces a novel hybrid framework integrating the Kashmiri Apple Optimization Algorithm (KAO) and the Arma...
An optimized scheduling system for surgical procedures is considered fundamental for maximizing hospital resource utilization and improving patient outcomes. The integration of Artificial Intelligence (AI) tools and New Technologies is paramount in t...
Manually converting unstructured text pathology reports into structured pathology reports is very time-consuming and prone to errors. This study demonstrates the transformative potential of generative AI in automating the analysis of free-text pathol...
Early detection of Diabetic Retinopathy (DR) is vital for preserving vision and preventing deterioration of eyesight. Fundus Fluorescein Angiography (FFA), recognized as the gold standard for diagnosing DR, effectively reveals abnormalities in retina...