IIOT

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April 2024
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Machine learning models predict ambulatory surgery end time, PACU discharge

Editor's Note In this study from the University of California, San Diego, La Jolla, researchers developed a machine learning model that improved the ability to predict surgery end times and PACU discharge at a range of start times in an ambulatory surgery center (ASC). Of 13,447 surgical procedures analyzed, the…

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By: Judy Mathias
June 29, 2022
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Machine learning model uses data from wearable devices to detect COVID-19 in HCWs

Editor's Note Researchers at the Icahn School of Medicine, Mount Sinai, New York City, have developed a machine learning model that uses physiological metrics collected from wearable devices that can detect and predict COVID-19 in healthcare workers (HCWs). A total of 407 HCWs from 7 hospitals were enrolled in the…

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By: Judy Mathias
June 23, 2022
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HHS issues new HIPPA guidance for audio-only telehealth services

Editor's Note On June 13, the Department of Health and Human Services (HHS) Office for Civil Rights (OCR) issued new guidance for HIPPA-covered healthcare providers and health plans to comply with privacy, security, and breach notification requirements when using remote communication technologies to provide “audio-only” telehealth services, the American Hospital…

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By: Tarsilla Moura
June 14, 2022
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New machine learning models predict adverse postop abdominal hernia surgery outcomes

Editor's Note Machine learning (ML) models designed by surgeons at the University of Texas MD Anderson Cancer Center in Houston show a high level of accuracy in predicting which types of patients are most likely to have a hernia recurrence or other complications after surgery in this study. Of 725…

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By: Judy Mathias
April 12, 2022
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Johns Hopkins robot performs first laparoscopic intestinal anastomosis without human help

Editor's Note The Smart Tissue Autonomous Robot (STAR), designed by a team of researchers at Johns Hopkins University, has performed laparoscopic intestinal anastomoses in four experiments on pig tissue without human help. The robot outperformed surgeons using manual-laparoscopic and robot-assisted surgical techniques in the consistency of suture spacing and bite…

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By: Judy Mathias
January 31, 2022
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Creating work schedules with AI reduces physician burnout

Editor's Note Artificial intelligence (AI)-based scheduling significantly improved physician engagement and reduced burnout, in this study presented by Ochsner Health researchers, January 28, at the American Society of Anesthesiologists’ ADVANCE 2022, the Anesthesiology Business Event, in Dallas. The AI-based scheduling software, which created fair and flexible schedules that supported work-life…

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By: Judy Mathias
January 31, 2022
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Patient safety and the “Internet of Medical Things (IoMT)”

With all of the advantages that come from electronic health records and connected devices, some distinct security risks also exist. Healthcare is seeing these risks grow in the form of ransomware, phishing attacks, and cybersecurity breaches. Healthcare has become one of the industries most vulnerable to cyberattacks, and one with…

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By: Karen Stockdale, MBA, BSN, RN
November 17, 2021
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AI examines gene-expression data to predict COVID-19 outcomes

Editor's Note In this study, researchers from the University of California, San Diego, developed an artificial intelligence (AI) algorithm to identify signature genes that forecast the severity of a viral infection immune response including that of COVID-19. The researchers analyzed more than 45,000 datasets from viral pandemics in humans, mice,…

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By: Judy Mathias
June 17, 2021
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Remote monitoring for ambulatory surgery patients reduces postop ED visits

Editor's Note This study by researchers at Memorial Sloan Kettering Cancer Center’s ambulatory surgery center, New York City, finds that remote measurement of patient-reported symptoms after surgery can improve outcomes and reduce postoperative urgent care and emergency department (ED) visits. The researchers developed an electronic platform and alert system, called…

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By: Judy Mathias
June 8, 2021
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AI tool detects COVID-19 by listening to patients’ coughs

Editor's Note Researchers from the Massachusetts Institute of Technology, Cambridge, have developed an artificial intelligence (AI) tool that can detect COVID-19 by listening to patients’ coughs, regardless if they are symptomatic or not. To build the tool, the researchers solicited audio recordings of patients coughing and accompanying information about their…

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By: Judy Mathias
November 10, 2020
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