Abstract Purpose of Review Computer-assisted diagnosis and treatment (CAD/CAT) is a
rapidly growing field of medicine that uses computer technology and telehealth to aid in the …

Clinical decision support systems (CDSS) aid health care professionals (HCP) in evaluating
large sets of information and taking informed decisions during their clinical routine. CDSS …

Class imbalance and the presence of irrelevant or redundant features in training data can
pose serious challenges to the development of a classification framework. This paper …

This work presents a computer-aided framework for allergy diagnosis which is capable of
handling comorbidities. The system was developed using datasets collected from allergy …

A framework for clinical diagnosis which uses bioinspired algorithms for feature selection
and gradient descendant backpropagation neural network for classification has been …

A computer‐aided diagnosis (CAD) system that employs a super learner to diagnose the
presence or absence of a disease has been developed. Each clinical dataset is …

Abstract Machine learning-aided medical decision making presents three major challenges:
achieving model parsimony, ensuring credible predictions, and providing real-time …

Introduction Artificial intelligence (AI) has an important role to play in future healthcare
offerings. Machine learning and artificial neural networks are subsets of AI that refer to the …

Abstract Purpose of Review Evidence-based clinical diagnosis of allergic disorders is
increasingly challenging. Clinical decision support systems implemented in mobile …

Allergic rhinitis (AR) is an antigen-mediated inflammation of the nasal mucosa that might
extend into the paranasal sinuses. Rhinorrhea, nasal obstruction or blockage, nasal itching …