Artificial intelligence (AI) has emerged as a crucial tool in healthcare with the primary aim of
improving patient outcomes and optimizing healthcare delivery. By harnessing machine …

Data are central to research, public health, and in develo** health information technology
(IT) systems. Nevertheless, access to most data in health care is tightly controlled, which …

Autonomous robotic surgery has the potential to provide efficacy, safety, and consistency
independent of individual surgeon's skill and experience. Autonomous anastomosis is a …

Since the publication of the first edition, parallel computing technology has gained
considerable momentum. A large proportion of this has come from the improvement in VLSI …

Background The benefits of using low-field-strength fetal MRI to evaluate antenatal
development include reduced image artifacts, increased comfort, larger bore size, and …

In recent years, several convolutional neural network (CNN) methods have been proposed
for the automated white matter lesion segmentation of multiple sclerosis (MS) patient …

The purpose of this book is to unify and document in one place many of the techniques and
much of the current understanding about solving systems of linear equations on vector and …

Lung ultrasound (LUS) has been increasingly expanding since the 1990s, when the clinical
relevance of vertical artifacts was first reported. However, the massive spread of LUS is only …

This study examines the impact of sample size on predicting cognitive and mental health
phenotypes from brain imaging via machine learning. Our analysis shows a 3-to 9-fold …

The most commonly used techniques for addressing each Emergency Department (ED)
problem (overcrowding, prolonged waiting time, extended length of stay, excessive patient …