Research

Cleveland Clinic Study Finds AI can Develop Treatments to Prevent "Superbugs"

Cleveland Clinic researchers developed an artficial intelligence (AI) model that can determine the best combination and timeline to use when prescribing drugs to treat a bacterial infection, based solely on how quickly the bacteria grow given certain perturbations. A team led by Jacob Scott, MD, PhD, and his lab in the Theory Division of Translational Hematology and Oncology, recently published their findings in PNAS.

New AI-Technology Estimates Brain Age Using Low-Cost EEG Device

As people age, their brains do, too. But if a brain ages prematurely, there is potential for age-related diseases such as mild-cognitive impairment, dementia, or Parkinson's disease. If "brain age" could be easily calculated, then premature brain aging could be addressed before serious health problems occur.

Researchers from Drexel University’s Creativity Research Lab developed an artificial intelligence (AI) technique that can effectively estimate an individual’s brain age based on electroencephalogram (EEG) brain scans.

ChatGPT Extracts Data for Ischaemic Stroke Almost Perfectly

In an ischaemic stroke, an artery in the brain is blocked by blood clots and the brain cells can no longer be supplied with blood as a result. Doctors must therefore act quickly and unblock the artery with the help of catheters. During the so-called mechanical thrombectomy, a lot of data has to be recorded and then transferred to various registers.

GPT-4 Matches Radiologists in Detecting Errors in Radiology Reports

Large language model GPT-4 matched the performance of radiologists in detecting errors in radiology reports, according to research published in Radiology, a journal of the Radiological Society of North America (RSNA).

Errors in radiology reports may occur due to resident-to-attending discrepancies, speech recognition inaccuracies and high workload. Large language models, such as GPT-4, have the potential to enhance the report generation process.

Experts Propose Specific and Suited Guidelines for the Use and Regulation of AI

Current Artificial Intelligence (AI) models for cancer treatment are trained and approved only for specific intended purposes. GMAI models, in contrast, can handle a wide range of medical data including different types of images and text. For example, for a patient with colorectal cancer, a single GMAI model could interpret endoscopy videos, pathology slides and electronic health record (EHR) data. Hence, such multi-purpose or generalist models represent a paradigm shift away from narrow AI models.

Can AI Techniques Help Clinicians Assess and Treat Patients with Bone Fractures?

Investigators have applied artificial intelligence (AI) techniques to gait analyses and medical records data to provide insights about individuals with leg fractures and aspects of their recovery.

The study, published in the Journal of Orthopaedic Research, uncovered a significant association between the rates of hospital readmission after fracture surgery and the presence of underlying medical conditions.

AI Makes Retinal Imaging 100 Times Faster

Researchers at the National Institutes of Health applied artificial intelligence (AI) to a technique that produces high-resolution images of cells in the eye. They report that with AI, imaging is 100 times faster and improves image contrast 3.5-fold. The advance, they say, will provide researchers with a better tool to evaluate age-related macular degeneration (AMD) and other retinal diseases.

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