The purpose of this literature review is to provide a fundamental synopsis of current research
pertaining to artificial intelligence (AI) within the domain of clinical practice. Artificial …

When a drug is administered to exert its efficacy, it will encounter multiple barriers and go
through multiple interactions. Predicting the drug-related multiple interactions is critical for …

The integration of deep learning techniques in pediatric neuroimaging has shown significant
promise in advancing various aspects of the field. This paper provides a comprehensive …

Artificial intelligence (AI) in medicine is transforming healthcare by automating system tasks,
assisting in diagnostics, predicting patient outcomes and personalising patient care …

The use of deep learning for identifying defects in medical images has rapidly emerged as a
significant area of interest across various medical diagnostic applications. The automated …

Complications of cancer therapy in children can result in a spectrum of neurologic toxicities
that may occur at the initiation of therapy or months to years after treatment. Although …

Background: Injury patterns in hypoxic-ischaemic brain injury (HIBI) are well recognised but
there are few studies evaluating cerebral injury using neuroquantification models …

Artificial intelligence (AI) as a technology that can increase efficiency and save human and
material resources is growing rapidly in the medical field. Due to its high accuracy and …

Simple Summary Diagnosis of posterior fossa tumors is challenging yet proper classification
is imperative given that treatment decisions diverge based on tumor type. The aim of this …