Artificial intelligence that detects surgical site infections from patient-submitted photos with 73% accuracy could enhance patient care and also reduce clinician burdens following surgeries.

In the current workflow for lung cancer patients, rapid genetic tests are often performed first. These tests use limited tumor tissue and leave about one in four patients without enough material for ...

A new clinical test may be able to predict which biologic may be the most effective for each individual with rheumatoid ...

Investigators have developed an artificial intelligence-assisted diagnostic system that can estimate bone mineral density in ...

This AI model from Mayo Clinic detects surgical site infections in wound images, improving early diagnosis and streamlining ...

Patient recruitment remains a major bottleneck in clinical trial execution, with inefficient patient-trial matching often causing delays and failures. Recent advancements in large language models ...

Kyruus Health is trying to solve the problem of care access through a nationwide platform, says President Paul Merrild.

Image AI automates document recognition and assigns incoming faxes to accurate patient records, then the staff reviews and approves the match.

#Eagles QB Jalen Hurts takes a few minutes before kickoff to surprise the patients at @ChildrensPhila who helped design his My Cause My Cleats with their own sneakers inspired by the design.

Precise detection of the corresponding fiducials in the image data is realized using an automated model-based matching algorithm on high-resolution, isometric cone beam CT images.

The myeloMATCH program will enroll patients into different studies as their cancer progresses, aiming to use precision medicine approaches to target residual disease.