Editor's Note The Food & Drug Administration (FDA) on December 30 announced a public workshop on the “Evolving Role of Artificial Intelligence [AI] in Radiological Imaging, which will take place February 25-26, 2020, at the Natcher Conference Center, National Institutes of Health, Bethesda, Maryland. The workshop will include discussions on…

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Editor's Note Integrating artificial intelligence (AI) with surgical decision making could transform care by augmenting the decision to perform surgery, informed consent process, identification and mitigation of modifiable risk factors, decisions on postoperative management, and shared decision for resource use, this review finds. Surgical decision making involves hypothetical-deductive reasoning, individual…

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Editor's Note Researchers at UT Southwestern Medical Center in Dallas have developed a new software tool that uses artificial intelligence (AI) to recognize cancer cells from digital pathology images, a December 9 UT Southwestern news release reports. The spatial distribution of different types of cells can reveal a cancer’s growth…

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Editor's Note GE Healthcare introduced the newest advancements in its Edison artificial intelligence (AI) programs and new imaging systems at the Radiological Society of North America’s annual meeting, the December 2 AuntMinnie.com reports. GE designed the Edison Open AI Orchestrator to simplify AI implementation and support of multiple AI applications…

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Editor's Note Two artificial intelligence-based algorithms predicted the probability of a patient dying in the ICU within 30 days of traumatic brain injury with accuracies up to 81% and 84%, in this study from Finland. The first algorithm is based on objective monitor data, and the second one includes data…

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Editor's Note Artificial intelligence (AI) was able to predict which patients were likely to develop an irregular heart rhythm, even when physicians interpreted results as normal, and identified patients at increased risk of dying of any cause within 1 year, in this study presented November 16 at the American Heart…

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Editor's Note In this study, a new machine learning Complexity Score algorithm outperformed three commonly used risk scores in predicting postoperative morbidity, 30-day readmission, 90-day readmission, and postoperative surper-use. Study patients underwent colectomy, abdominal aortic aneurysm repair, coronary artery bypass grafting, total hip or knee replacement, or lung resection. The…

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Editor's Note Heartvista (Los Altos, California) has obtained clearance from the Food and Drug Administration (FDA) for its artificial intelligence (AI)-assisted One Click autonomous MRI acquisition software for cardiac ischemia exams, the October 30 BioWorld MedTech reports. Integrated with existing MRI scanners, the software uses AI to guide image acquisition,…

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Editor's Note Artificial intelligence (AI) in the form of a machine-learned algorithm correctly triaged the vast majority of postoperative patients to the ICU, in this pilot study presented October 29 at the American College of Surgeons Clinical Congress 2019 in San Francisco. The algorithm included 87 clinical variables and 15…

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Editor's Note In this study, machine learning algorithms accurately identified cancer patients who were at risk of 6-month mortality. Of 26,525 cancer patients analyzed, machine learning models based on structured electronic health record data accurately predicted short-term mortality risk with good discrimination and positive predictive value. When the gradient boosting…

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