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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non-small cell lung cancer tumor segmentation

Algorithm reduces NSCLC tumor segmentation times by 65%

In a close collaboration with radiation oncologists, experts trained their model on the CT lung images of 787 patients and tested it on the scans of more than 1,300 patients from external datasets.

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InterWell Health completes $2.4B three-way merger with Fresenius, Cricket Health

InterWell Health has completed its merger with Fresenius Health Partners and Cricket Health in a deal valued at $2.4 billion. The three-way merger was originally announced in March 2022. 

women burnout

AI model explores EHR data to predict physician burnout

A new AI tool from Washington University in St. Louis researchers aims to help identify burnout among physicians and could potentially prevent it in the future.

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AI identifies Parkinson’s from breathing patterns

The tool could help alleviate the disease onset gap between when symptoms of Parkinson’s first appear and when most people receive a diagnosis.

AI research published without code, data, documentation interesting to readers but unhelpful to science: RSNA pubs review

Over the five-year period ending last December 31, only a third of 218 scientific articles on AI in four popular radiology journals shared the researchers’ code. 

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Clinical evidence is limited in many AI product promotions, analysis shows

To promote the legitimacy of their products, companies most often tout their partnerships with medical and academic institutions, in addition to their applications’ legal approvals.

Julius Bogdan, vice president and general manager of the Healthcare Information and Management Systems Society (HIMSS) Digital Health Advisory Team for North America, explains considerations for healthcare system information technology (IT) management teams on the implementation of artificial intelligence (AI). He also discusses ideally how AI should be integrated into medical IT systems, and some of the issues AI presents in the complex environment of real-world patient care." #AI #HIMSS

VIDEO: How hospital IT teams should manage implementation of AI algorithms

Julius Bogdan, vice president and general manager of the HIMSS Digital Health Advisory Team for North America, explains considerations for healthcare IT teams on the implementation of artificial intelligence (AI).

Bibb Allen, MD, FACR, chief medical officer of the American College of Radiology (ACR) Data Science Institute, and former ACR president, explains how hospitals or radiology departments can conduct quality assurance (QA) assessments on artificial intelligence (AI) algorithms they adopt to ensure they are accurate. The ACR established the Assess-AI Registry and AI-Lab to help with validating and tracking AI QA for FDA-cleared algorithms.

VIDEO: Validation monitoring for radiology AI to ensure accuracy

Bibb Allen, MD, FACR, Chief Medical Officer of the American College of Radiology (ACR) Data Science Institute, and former ACR president, explains how hospitals or radiology departments can conduct quality assurance assessments on artificial intelligence algorithms they adopt to ensure they are accurate. 

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