Tag: Information Systems

Improving prediction of adverse surgical outcomes with machine learning algorithm

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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By: Judy Mathias
November 6, 2019
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ACS NSQIP risk calculator predicts four outcomes for geriatric surgical patients

Editor's Note The American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) Surgical Risk Calculator accurately predicted four quality-of-life outcomes that transcend traditional measures of successful surgery and now reflects the expected effects of surgery on an older patient’s ability to function independently, finds this study presented October…

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By: Judy Mathias
November 5, 2019
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FDA clears Heartvista’s AI-assisted cardiac MRI tool

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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By: Judy Mathias
November 5, 2019
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Joint Commission: Deadline approaching for submission of CY 2019 eCQM data

Editor's Note The Joint Commission on October 29 announced that the deadline for onboarding to the Direct Data Submission (DDS) Platform for submission of CY 2019 electronic clinical quality measures (eCQMs) is December 20. Organizations that submitted CY 2018 eCQMs through the DDS Platform do not need to be onboarded…

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By: Judy Mathias
October 31, 2019
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Can machine learning predict 6-month mortality in cancer patients?

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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By: Judy Mathias
October 28, 2019
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Radiologist, AI combination improves breast cancer detection

Editor's Note An artificial intelligence (AI) model was able to detect breast cancer with nearly 90% accuracy when combined with analysis from radiologists, the October 18 Health IT Analytics reports. Researchers from New York University Schools of Medicine and Data Science developed the model to first consider small patches of…

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By: Judy Mathias
October 21, 2019
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Robotic-arm assisted TKA: A growing and promising technology

  Total knee arthroplasty (TKA) is a highly effective treatment for end-stage degenerative joint disease and has helped patients regain functional mobility with reduced pain and improved quality of life. Every year, almost 700,000 primary TKA procedures are performed in the US.1 This number is expected to grow to 3.48…

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By: Kevin Barga, MS, RN, CCRP
October 21, 2019
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Will the success of AI in healthcare depend on nurses?

Editor's Note Nurses have always played an important role when new health information technology (IT) has been implemented, and the emergence of artificial intelligence (AI) and the changes it can bring to healthcare will be no exception, reports the September 27 HealthcareITNews. Though some nurses may view AI as another…

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By: Judy Mathias
October 7, 2019
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AI detects key findings in chest x-rays of pneumonia patients within 10 seconds

Editor's Note Researchers from Intermountain Healthcare and Stanford University say 10 seconds is how long it takes for their new model, which uses artificial intelligence (AI), to accurately identify key findings in chest x-rays of patients in the emergency department suspected of having pneumonia. The researchers presented the findings of…

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By: Judy Mathias
September 30, 2019
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AI predicts radiation therapy side effects for head and neck cancer patients

Editor's Note A computer model, which for the first time accurately predicted two of the most challenging side effects of radiation therapy for head and neck cancer patients, was presented September 26 at the Annual Meeting of the American Society for Radiation Oncology in Chicago. Researchers from the University of…

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By: Judy Mathias
September 30, 2019
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