In a recent study published in The Lancet Digital Health, researchers discuss the development and validation of a combined model comprising imaging, clinical, and cell-free deoxyribonucleic acid (DNA) ...

With the help of machine learning, scientists have identified a plethora of previously-unidentified drug targets for breast cancer, cervical cancer, glioblastoma and more. In a study published Jan. 11 ...

Artificial intelligence is no longer just spotting tumors a little faster than humans. In study after study, machine learning systems are uncovering hidden patterns in cancer data that even veteran ...

Patient and Caregiver Perceptions of an Interface Design to Communicate Artificial Intelligence–Based Prognosis for Patients With Advanced Solid Tumors Clinical trial data were used and contained ...

For over three decades, a highly accurate early diagnostic test for ovarian cancer has eluded physicians. Now, scientists in the Georgia Tech Integrated Cancer Research Center (ICRC) have combined ...

Craif Inc. in Nagoya, Japan, working with Nagoya University's Institute of Innovation for Future Society, has developed a ...

Researchers developed and validated a machine-learning algorithm for predicting nutritional risk in patients with nasopharyngeal carcinoma.

Researchers created a model that uses clinical testing data to locate the primary site of cancer cells with no known origin, likely improving survival. Using NGS data from 36,445 tumor samples with ...

While the buzz around generative AI continues to build, physicians at advanced cancer centers, startups and biomedical companies are seeing the potential for gen AI solutions to advance cancer ...

The manufacturing process for personalized T-cell therapies hardly begins before it stalls. Why? Right at the start, there is a severe bottleneck: the need to identify patient-derived, tumor-reactive ...