As healthcare systems around the world face challenges such as escalating costs, limited
access, and growing demand for personalized care, artificial intelligence (AI) is emerging as …

With the development of modern high-throughput omic measurement platforms, it has
become essential for biomedical studies to undertake an integrative (combined) approach to …

The personalized titration and optimization of insulin regimens for treatment of type 2
diabetes (T2D) are resource-demanding healthcare tasks. Here we propose a model-based …

Multimodal medical data fusion has emerged as a transformative approach in smart
healthcare, enabling a comprehensive understanding of patient health and personalized …

With the advances of data-driven machine learning research, a wide variety of prediction
problems have been tackled. It has become critical to explore how machine learning and …

Sustainable smart cities aim to optimize projected complexities, costs, and environmental
challenges accompanied by growing urbanization. The fundamental objectives of …

Pancreatic cancer is the deadliest disease, with a five-year overall survival rate of just 11%.
The pancreatic cancer patients diagnosed with early screening have a median overall …

Today, artificial intelligence (AI) and machine learning (ML) have dramatically advanced in
various industries, especially medicine. AI describes computational programs that mimic and …

Healthcare prediction has been a significant factor in saving lives in recent years. In the
domain of health care, there is a rapid development of intelligent systems for analyzing …

The increasing access to health data worldwide is driving a resurgence in machine learning
research, including data-hungry deep learning algorithms. More computationally efficient …