Emotion recognition is the ability to precisely infer human emotions from numerous sources
and modalities using questionnaires, physical signals, and physiological signals. Recently …

Healthcare traditionally relies on single-modality approaches, which limit the information
available for medical decisions. However, advancements in technology and the availability …

Background Hypertension is a crucial health indicator because it provides subtle details
about a patient's cardiac health. Photoplethysmography (PPG) signals are a critical …

Positron emission tomography/computed tomography (PET/CT) is increasingly used in
oncology, neurology, cardiology, and emerging medical fields. The success stems from the …

Despite major advances in artificial intelligence (AI) for medicine and healthcare, the
deployment and adoption of AI technologies remain limited in real-world clinical practice. In …

The proliferation of various forms of artificial intelligence (AI) brings many opportunities to
improve health care. AI models can harness complex evolving data, inform and augment …

The frequency and unpredictability of natural disasters pose serious challenges to
emergency management in modern society. Effective emergency management requires not …

Cardiovascular diseases (CVDs) are the leading cause of death globally. The use of artificial
intelligence (AI) methods—in particular, deep learning (DL)—has been on the rise lately for …

Ensemble models have emerged as a powerful technique for improving robustness in
medical image segmentation. However, traditional ensembles suffer from limitations such as …

Background and objectives Non-alcoholic fatty liver disease (NAFLD) is a common liver
disease with a rapidly growing incidence worldwide. For prognostication and therapeutic …