Abstract The Internet of Things (IoT) and artificial intelligence (AI) are two of the fastest-
growing technologies in the world. With more people moving to cities, the concept of a smart …

Objective This article methodically reviews the literature on deep learning (DL) for natural
language processing (NLP) in the clinical domain, providing quantitative analysis to answer …

Deep learning techniques have found applications across diverse fields, enhancing the
efficiency and effectiveness of decision-making processes. The integration of these …

Artificial Intelligence techniques such as Machine Learning (ml) have not been exploited to
their maximum potential in the legal domain. This has been partially due to the insufficient …

Background Appropriate anticoagulant therapy for patients with atrial fibrillation (AF)
requires assessment of stroke and bleeding risks. However, risk stratification schemas such …

Objectives A substantial portion of the data contained in Electronic Health Records (EHR) is
unstructured, often appearing as free text. This format restricts its potential utility in clinical …

Smarthealth care system is required to handle the large volume of data produced by the
Massive Internet of Medical things. Smart healthcare system uses information and …

Purpose Traditional Chinese medicine (TCM) prescriptions have always relied on the
experience of TCM doctors, and machine learning (ML) provides a technical means for …

Algorithms are increasingly employed to provide highly accurate advice and
recommendations across domains, yet in many cases people tend to prefer human advisors …

A lot of focus has recently been placed on clinical decision support systems, that use
advanced data mining methods to assist clinicians in making wise decisions. Along with …