In healthcare, the development and deployment of insufficiently fair systems of artificial
intelligence (AI) can undermine the delivery of equitable care. Assessments of AI models …

Artificial intelligence (AI) with deep learning models has been widely applied in numerous
domains, including medical imaging and healthcare tasks. In the medical field, any judgment …

Artificial intelligence (AI) is currently being utilized in a wide range of sophisticated
applications, but the outcomes of many AI models are challenging to comprehend and trust …

In oncology, the patient state is characterized by a whole spectrum of modalities, ranging
from radiology, histology, and genomics to electronic health records. Current artificial …

Widespread adoption of artificial intelligence (AI) technologies is substantially affecting the
human condition in ways that are not yet well understood. Negative unintended …

Artificial intelligence (AI) methods have multiplied our capabilities to extract quantitative
information from digital histopathology images. AI is expected to reduce workload for human …

Artificial Intelligence (AI) techniques of deep learning have revolutionized the disease
diagnosis with their outstanding image classification performance. In spite of the outstanding …

Deep Learning (DL), a groundbreaking branch of Machine Learning (ML), has emerged as a
driving force in both theoretical and applied Artificial Intelligence (AI). DL algorithms, rooted …

A growing number of artificial intelligence (AI)-based clinical decision support systems are
showing promising performance in preclinical, in silico, evaluation, but few have yet …

Abstract Federated Learning (FL), Artificial Intelligence (AI), and Explainable Artificial
Intelligence (XAI) are the most trending and exciting technology in the intelligent healthcare …