Machine learning (ML) is increasingly used in clinical oncology to diagnose cancers, predict
patient outcomes, and inform treatment planning. Here, we review recent applications of ML …

Purpose Artificial intelligence (AI) models are playing an increasing role in biomedical
research and healthcare services. This review focuses on challenges points to be clarified …

Introduction Artificial intelligence (AI) and machine learning (ML) are rapidly evolving fields
in various sectors, including healthcare. This article reviews AI's present applications in …

In the past decade, advances in precision oncology have resulted in an increased demand
for predictive assays that enable the selection and stratification of patients for treatment. The …

Background Several studies highlight the effects of artificial intelligence (AI) systems on
healthcare delivery. AI-based tools may improve prognosis, diagnostics, and care planning …

Introduction Recent developments in the field of Artificial Intelligence (AI) applied to
healthcare promise to solve many of the existing global issues in advancing human health …

Discovering new treatments and personalizing existing ones is one of the major goals of
modern clinical research. In the last decade, Artificial Intelligence (AI) has enabled the …

One of the most promising areas of health innovation is the application of artificial
intelligence (AI), primarily in medical imaging. This article provides basic definitions of terms …

In this white paper, experts from the Digital Pathology Association (DPA) define terminology
and concepts in the emerging field of computational pathology, with a focus on its …

The increasing application of Artificial Intelligence (AI) in health and medicine has attracted
a great deal of research interest in recent decades. This study aims to provide a global and …