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. 

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Machine learning predicts heart attack with 94% accuracy

Chest pain is one of the most common reasons patients visit the emergency department (ED), but relatively few are eventually diagnosed with myocardial infarction (MI). New research found a machine learning algorithm can predict MI with 94 percent accuracy.

Healthcare aims to improve utilization of AI

The healthcare industry is poised to see a 40 percent increase in the artificial intelligence (AI) market in the coming years—and, despite heavy regulations, the industry continues to improve utilization.

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AI algorithm prevents spread of infectious diseases

Researchers from the University of Southern California Viterbi School of Engineering have developed an algorithm capable of slowing the spread of infectious diseases while accounting for limited resources and population dynamics. Findings are published in the AAAI Conference on Artificial Intelligence.

Using AI, deep learning to fight aging

A Baltimore-based company is utilizing the power of artificial intelligence (AI) and deep learning to advance drug discovery, biomarker development and aging research.

Apple Watch detects individuals with diabetes with 85% accuracy

Researchers at the University of California, San Francisco and digital health startup Cardiogram have found the Apple Watch capable of detecting patients with diabetes with 85 percent accuracy.

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Deep learning algorithm identifies candidates for palliative care—and predicts death

A novel deep learning algorithm could hold the key to proactive palliative care—and predict patient deaths, according to a paper published by the Stanford University School of Medicine in California.

64% of patients excited about AI-powered nurse assistants

As artificial intelligence (AI) becomes more advanced and commonplace in medicine, patients are excited about the possibilities the technology could bring to care, according to a report released by Syneos Health Communications.

Medopad startup uses large populations in China to train AI

The healthcare technology startup Medopad, which developed a tool for clinicians to track the vital signs, has used large populations from China to improve the predictive analytics of their artificial intelligence (AI).

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Q&A: MedAxiom CEO explores key trends in cardiologist, cardiovascular surgeon compensation

Compensation for heart specialists continues to climb. What does this say about cardiology as a whole? Could private equity's rising influence bring about change? We spoke to MedAxiom CEO Jerry Blackwell, MD, MBA, a veteran cardiologist himself, to learn more.

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Payment cuts and beyond: Key takeaways for cardiologists from the 2025 Medicare Physician Fee Schedule

The American College of Cardiology has shared its perspective on new CMS payment policies, highlighting revenue concerns while providing key details for cardiologists and other cardiology professionals. 

AI in Healthcare
A modest proposal to rally AI regulators around a simple game plan

As debate simmers over how best to regulate AI, experts continue to offer guidance on where to start, how to proceed and what to emphasize. A new resource models its recommendations on what its authors call the “SETO Loop.”