Artificial Intelligence

Artificial intelligence (AI) is becoming a crucial component of healthcare to help augment physicians and make them more efficient. In medical imaging, it is helping radiologists more efficiently manage PACS worklists, enable structured reporting, auto detect injuries and diseases, and to pull in relevant prior exams and patient data. In cardiology, AI is helping automate tasks and measurements on imaging and in reporting systems, guides novice echo users to improve imaging and accuracy, and can risk stratify patients. AI includes deep learning algorithms, machine learning, computer-aided detection (CAD) systems, and convolutional neural networks.

5 benefits of AI-enabled EHR systems
Integrating AI into the electronic medical record can make patient data more usable and dependable for end-users, according to a review of the relevant scientific literature published this month in the American Journal of Clinical and Medical Research.
Prompts matter: How input elements affect large language model performance
Just like radiologists, the performance of large language models improves when given proper context.
AI can help radiology standardize image exam data labeling
To fully leverage today's radiology IT systems, standardization is a necessity. Steve Rankin, chief strategy officer for Enlitic, explains how artificial intelligence can help.
FDA regulator examines AI's growing influence in cardiology
Stephen Browning, the FDA's assistant director of hemodynamics and heart failure diagnostics, spoke with Cardiovascular Business about the agency's perspective on AI-enabled cardiovascular devices and many other topics.
Industry Watcher’s Digest
HHS isn’t waiting to see what its incoming secretary does before filling some key leadership positions.

ai enabled electronic health record EHR EMR

5 benefits of AI-enabled EHR systems

Integrating AI into the electronic medical record can make patient data more usable and dependable for end-users, according to a review of the relevant scientific literature published this month in the American Journal of Clinical and Medical Research.

artificial intelligence healthcare industry digest

Prompts matter: How input elements affect large language model performance

Just like radiologists, the performance of large language models improves when given proper context.

Video of Steve Rankin, chief strategy officer for Enlitic, explaining how AI can help standardize labeling of medical images.

AI can help radiology standardize image exam data labeling

To fully leverage today's radiology IT systems, standardization is a necessity. Steve Rankin, chief strategy officer for Enlitic, explains how artificial intelligence can help.

Stephen Browning, FDA assistant director for hemodynamic and heart failure diagnostics, explains the FDA perspectives and regulatory pathways for AI-enabled cardiovascular devices at TCT 2024.

FDA regulator examines AI's growing influence in cardiology

Stephen Browning, the FDA's assistant director of hemodynamics and heart failure diagnostics, spoke with Cardiovascular Business about the agency's perspective on AI-enabled cardiovascular devices and many other topics.

Industry Watcher’s Digest

HHS isn’t waiting to see what its incoming secretary does before filling some key leadership positions.

AI uncovers ‘vascular fingerprints’ in the eye that can predict strokes

An advanced algorithm was trained to evaluate more than 100 different details about the inside of a patient's eye. Its ability to identify high-risk patients was comparable to more traditional techniques, exciting researchers.

AI in the ICU (and elsewhere): Less stress, better conditions, alleviated shortages

When appropriately applied in critical care settings, AI can deliver considerable value to clinical staff, hospital management and local communities. In the process the technology may help resolve persistent staffing shortages.

Mayo Clinic and Microsoft partner to advance generative AI in radiology

The pair's hope is that their model, which will first focus on chest X-rays, will provide significant benefits for radiology workflows.