Radiomics analysis has had remarkable progress along with advances in medical imaging,
most notability in central nervous system malignancies. Radiomics refers to the extraction of …

Abstract The role of Artificial Intelligence and Machine Learning in cancer research offers
several advantages, primarily scaling up the information processing and increasing the …

Surgical robots have been widely adopted with over 4000 robots being used in practice
daily. However, these are telerobots that are fully controlled by skilled human surgeons …

Purpose To analyze baseline CT/MR-based image features of salivary glands to predict
radiation-induced xerostomia 3-months after head-and-neck cancer (HNC) radiotherapy …

The recent explosion in machine learning efforts in the quality assurance (QA) space has
produced a variety of proofs‐of‐concept many with promising results. Expected outcomes of …

For nearly 2 decades, adaptive radiation therapy (ART) has been proposed as a method to
account for changes in head and neck tumor and normal tissue to enhance therapeutic …

Cancer care is moving from a disease‐focused management toward a patient‐centered
tailored approach. Multidisciplinary management that aims to define individual, optimal …

Radiotherapy aims to achieve a high tumor control probability while minimizing damage to
normal tissues. Personalizing radiotherapy treatments for individual patients, therefore …

Objectives Learning health systems (LHS) integrate knowledge and practice through cycles
of continuous quality improvement and learning to increase healthcare quality. LHS have …

In this paper, we present a framework for develo** a Learning Health System (LHS) to
provide means to a computerized clinical decision support system for allied healthcare …