The development of new therapeutic strategies such as immune checkpoint inhibitors (ICIs) and targeted therapies has increased the complexity of the treatment landscape for solid tumors. At the current rate of annual FDA approvals, the potential trea...
BACKGROUND: Artificial intelligence broadly refers to computer systems that simulate intelligent behaviour with minimal human intervention. Emphasizing patient-centered care, research has explored patients' perspectives on artificial intelligence in ...
BACKGROUND AND OBJECTIVES: Having a sufficient sample size is crucial when developing a clinical prediction model. We reviewed details of sample size in studies developing prediction models for binary outcomes using machine learning (ML) methods with...
The international journal of cardiovascular imaging
Jan 13, 2025
Coronary artery calcification (CAC) is a key marker of coronary artery disease (CAD) but is often underreported in cancer patients undergoing non-gated CT or PET/CT scans. Traditional CAC assessment requires gated CT scans, leading to increased radia...
BACKGROUND: Deep learning (DL) has set new standards in cancer diagnosis, significantly enhancing the accuracy of automated classification of whole slide images (WSIs) derived from biopsied tissue samples. To enable DL models to process these large i...
Graph representation learning has been leveraged to identify cancer genes from biological networks. However, its applicability is limited by insufficient interpretability and generalizability under integrative network analysis. Here we report the dev...
PURPOSE: Enhancing the speed and efficiency of clinical trial recruitment is a key objective across international health systems. This study aimed to use artificial intelligence (AI) applied in the Victorian Cancer Registry (VCR), a population-based ...
Molecular characterization of tumors is essential to identify predictive biomarkers that inform treatment decisions and improve precision immunotherapy development and administration. However, challenges such as the heterogeneity of tumors and patien...
Clinical oncology (Royal College of Radiologists (Great Britain))
Jan 8, 2025
Artificial intelligence (AI) advancements have accelerated applications of imaging in clinical oncology, especially in revolutionizing the safe and accurate delivery of state-of-the-art imaging-guided radiotherapy techniques. However, concerns are gr...
The American journal of clinical nutrition
Jan 8, 2025
BACKGROUND: Cachexia is associated with multiple adverse outcomes in cancer. However, clinical decision-making for oncology patients at the cachexia stage presents significant challenges.