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. 

Microsoft Johns Hopkins AI partnership

7 lessons learned during joint big business/healthcare AI projects

Big Tech players have been investing in partnerships with large healthcare providers on AI endeavors for several years now. According to both sides in one such collaboration, the resulting synergy offers “immense potential” to improve patient access, care and outcomes.

An overview of artificial intelligence (AI) in radiology with Keith Dreyer with the ACR. Images shows a COVID-19 lung CT scan reconstruction from Siemens Healthineers. #AI #radAI #ACR

Artificial intelligence shows promise in mitigating radiologist bias

AI clinical decision support was particularly popular among younger radiologists, experts wrote in Scientific Reports

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AI aids nonphysicians in obtaining diagnostic-quality ultrasound images in the ED

Registered nurses, NPs and EMTs bolstered the quality of their scans with the help of deep learning-based guidance.

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'Quite impressive': ChatGPT generates a nuclear medicine report

The generated report included indication, findings laid out numerically, TNM stage, impression and follow-up recommendations.

Nearly all health leaders are investing in software this year

A whopping 94% of health leaders in the survey said they plan to invest in software this year, partly to fend off clinician burnout and a looming recession.

AI predicts mortality risk based on ECG results with 85% accuracy

The model estimated mortality risk for more than 244,000 patients in Alberta, Canada, who had an ECG taken after a related health incident. 

Emergency physician in COVID mask

Study supports feasibility of full-time AI-based workflow in the ED

When used to flag anomalies in combined chest and musculoskeletal X-rays, imaging AI can relieve overstretched emergency radiology teams.

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Radiologists outperform commercially available AI in PI-RADS scoring

The findings contradict prior research that utilized the same software, experts involved in the research noted. This could be due to out-of-distribution data for the DL software, which could impair its performance.