EurekAlert: Artificial intelligence can dramatically cut time needed to process abnormal chest X-rays

EurekAlert: Artificial intelligence can dramatically cut time needed to process abnormal chest X-rays . “New research has found that a novel Artificial Intelligence (AI) system can dramatically reduce the time needed to ensure that abnormal chest X-rays with critical findings will receive an expert radiologist opinion sooner, cutting the average delay from 11 days to less than 3 days. Chest X-rays are routinely performed to diagnose and monitor a wide range of conditions affecting the lungs, heart, bones, and soft tissues.”

EurekAlert: Machine learning could reduce testing, improve treatment for intensive care patients

EurekAlert: Machine learning could reduce testing, improve treatment for intensive care patients . “Doctors in intensive care units face a continual dilemma: Every blood test they order could yield critical information, but also adds costs and risks for patients. To address this challenge, researchers from Princeton University are developing a computational approach to help clinicians more effectively monitor patients’ conditions and make decisions about the best opportunities to order lab tests for specific patients.”

Science Blog: Artificial Intelligence And The Future Of Medicine

Science Blog: Artificial Intelligence And The Future Of Medicine. “Washington University researchers are working to develop artificial intelligence (AI) systems for health care, which have the potential to transform the diagnosis and treatment of diseases, helping to ensure that patients get the right treatment at the right time.”

EurekAlert: Reliance on ‘YouTube medicine’ may be dangerous for those concerned about prostate cancer

EurekAlert: Reliance on ‘YouTube medicine’ may be dangerous for those concerned about prostate cancer . “The most popular YouTube videos on prostate cancer often offer misleading or biased medical information that poses potential health risks to patients, an analysis of the social media platform shows.”

STAT News: As social media ‘influencers,’ patients are getting a voice. And pharma is ready to pay up

STAT News: As social media ‘influencers,’ patients are getting a voice. And pharma is ready to pay up. “Anne Marie Ciccarella is not a doctor, though she spends a great deal of time with them. She’s not a researcher, though she routinely pores over scientific papers on cancer. And even though she spent most of her career at an accounting firm, she’s getting paid by drug companies for her opinions. Ciccarella is one of a growing number of people who have leveraged their experiences as patients and the loyal followings they’ve built on social media into a career, no matter how small their audience.”

Georgia Tech: Open Source Machine Learning Tool Could Help Choose Cancer Drugs

Georgia Tech: Open Source Machine Learning Tool Could Help Choose Cancer Drugs. “The selection of a first-line chemotherapy drug to treat many types of cancer is often a clear-cut decision governed by standard-of-care protocols, but what drug should be used next if the first one fails? That’s where Georgia Institute of Technology researchers believe their new open source decision support tool could come in. Using machine learning to analyze RNA expression tied to information about patient outcomes with specific drugs, the open source tool could help clinicians chose the chemotherapy drug most likely to attack the disease in individual patients.”

Columbia Journalism Review: Sarah Kliff brings transparency to ER prices, one hospital bill at a time

Columbia Journalism Review: Sarah Kliff brings transparency to ER prices, one hospital bill at a time . “IT STARTED WITH A BAND-AID. A $629 Band-Aid. A medical bill emailed to Vox senior policy correspondent Sarah Kliff got her interested in emergency room facility fees—a widely applied, highly variable, and little understood cost in the healthcare system. The fees, set between hospitals and insurers, are the charge from the hospital for coming in for treatment. Last October, Kliff set out to learn more about these fees through one of the only ways she could think of to get the information: by collecting hospital bills.”