MedicalXPress: New online database has answers on mitochondrial disorders

MedicalXPress: New online database has answers on mitochondrial disorders. “Michigan State University biochemist Laurie Kaguni and her team have created a new tool—the POLG Pathogenicity Prediction Server – to help clinicians and scientists better diagnose POLG disorders and more accurately predict their outcomes. The tool is featured in BBA Clinical. Because of their central role in cellular energy production and multiple metabolic processes, mitochondrial diseases can affect organs, motor function and the nervous system. The wide spectrum of symptoms presented by these disorders poses significant challenges to their diagnosis. The database contains 681 anonymous POLG patient entries gathered from publicly available case reports. Each patient entry includes data on age of diagnosis and symptoms present.”

Wired: Medicine Is Going Digital. The FDA Is Racing to Catch Up

Wired: Medicine Is Going Digital. The FDA Is Racing to Catch Up. “Today, machine learning powers more and more medical device software. And because it is always learning and improving, it is constantly changing products on the fly. For most regulators, an ever-changing algorithm is their worst nightmare. But [Bakul] Patel is one of those rare Washington bureaucrats who’s also a fervently optimistic futurist. And he’s got big plans to get federal regulators off Washington time and up to Silicon Valley speeds.”

University of Chicago: UChicago Medicine collaborates with Google to use machine learning for better health care

University of Chicago: UChicago Medicine collaborates with Google to use machine learning for better health care. “The University of Chicago Medicine is collaborating with Google to study ways to use data in electronic medical records to make discoveries that could improve the quality of health care. The work focuses on using new machine-learning techniques to create predictive models that could help prevent unplanned hospital readmissions, avoid costly complications and save lives.”

Fierce Pharma: Newly beefed up in antibiotics, Pfizer launches user-friendly access to global resistance database

Fierce Pharma: Newly beefed up in antibiotics, Pfizer launches user-friendly access to global resistance database. “ATLAS tracks a wide array of pathogens and antibiotic treatments, allowing doctors, healthcare providers, researchers and even average consumers to look at what’s happening in their own backyards. A physician prescribing an antibiotic to a patient for a known infection, for example, can look up resistance rates and trends for the drugs they’re considering—all the way down to the regional and state level.”

From Opioids To Silica Gel: Interactive Online Tool Provides Immediate Advice For Poison-Related Emergencies (PRESS RELEASE)

A new Web site aims to provide advice for poison-related emergencies (PRESS RELEASE). “The new tool provides critical, lifesaving poison information from any computer or smart device. The nation’s 55 poison control centers, collectively known as ‘poison control,’ are staffed by specially-trained physicians, pharmacists, and nurses who are experts in toxicology, poisoning information, prevention, and treatment—many of these same experts created and vetted the new online tool. “

PRN: Philips and LabPON plan to create world’s largest pathology database of annotated tissue images for deep learning (PRESS RELEASE)

In development: a database of annotated tissue images (PRESS RELEASE). “Royal Philips (NYSE: PHG, AEX: PHIA) and LabPON, the first clinical laboratory to transition to 100 percent histopathology digital diagnosis, today announced its plans to create a digital database of massive aggregated sets of annotated pathology images and big data utilizing Philips IntelliSite Pathology Solution… As one of the largest pathology laboratories in the Netherlands, LabPON will contribute its repository of approximately 300,000 whole slide images (WSI) they prospectively create each year to the database. This will contain de-identified datasets of annotated cases that are manually commented by the pathologist, and will comprise of a wide variety of tissue and disease types, as well as other pertinent diagnostic information to facilitate deep learning.”