Latest AI and machine learning research in other cancers for healthcare professionals.
The performance and generalisability of machine learning (ML) models relies on high-quality data. Re...
Soft tissue sarcomas (STS) histopathological classification system has several conceptual caveats, i...
To evaluate the potential of wrist-worn wearable devices to detect and quantify Faciobrachial Dyston...
Conventional chemotherapeutics exploit cancer’s hallmark of active cell cycling, primarily targeting...
Artificial Intelligence (AI) has demonstrated a high image processing capacity and improved diagnost...
Large-scale cohort studies exploring the etiology of obstructive jaundice (OJ) are scarce, with curr...
Machine learning (ML) applications within diagnostic histopathology have been extremely successful. ...
To synthesize existing literature on patient attitudes toward AI in cancer care and identify knowled...
Sleep quality is vital to human health, yet automated sleep staging faces challenges in cross-center...
Breast cancer is one of the leading causes of cancer-related mortality among women worldwide. Despit...
This study explores the multi-level regulatory roles of the lactate metabolism gene network in oral ...
Neoantigens have emerged as promising targets for personalized cancer immunotherapy. However, accura...
Extracting structured data from free-text medical records at scale is laborious, and traditional app...
Multiple myeloma (MM) is the second most common hematologic malignancy in the U.S., with Black patie...
T1w/T2w ratio mapping, combining voxel-wise signal intensities in T1-weighted (T1w) and T2-weighted ...
Liquid biopsies and cell-free DNA (cfDNA) offer minimally invasive methods for the diagnosis and mon...
Adjuvant use of bone-modifying agents (BMAs) to early-stage breast cancer (eBC) aims to maintain bon...
Annotation of liver biopsies, for disease staging is increasingly aided by digital pathology, howeve...
Advanced-stage disease at the time of diagnosis, with resultant high mortality, is among the most ur...
In this study, we develop and validate an interpretable machine learning (ML) model that integrates ...
Accurate data resources are essential for impactful medical research, but available structured datas...