Diagnostic Reading #20: Five “Must Read” Articles on HIT and Radiology

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Radiology training and physician follow up are in the news this week.

This week’s articles in Diagnostic Reading include: medical students aren’t receiving enough radiology training; an expert’s view on machine learning; radiologists and their responsibility for physician follow through; a new machine learning tool that may detect fatal strains of bacteria; and an Alzheimer’s study that reveals a difference in disease development between genders.

Residency program directors agree: medical students don’t receive enough radiology training – Radiology Business

Medical students today are largely unprepared for standard radiologic interpretation as interns, according to recently published research in Academic Radiology. Though published guidelines for med school curricula exist, the study’s authors stated that they’re often ignored, resulting in a massive variation of what is taught to medical students—and how—across the country.

An expert’s take on the future of machine learning in quantitative image analysis – Health Imaging

Diagnostic Reading summarizes the latest radiology and healthcare IT news.

Current and future clinical use and real-world applications of artificial intelligence (AI) technology in healthcare and medicine will take center stage when new research, startups, scientists and industry leaders get together in June for the AI in Healthcare Summit. This article spotlights one of the speakers, who discusses his work with machine learning and quantitative medical image analysis.

Can a radiologist be sued for failing to follow up with a referring physician? – Radiology Business

In an imaging landscape where 64 percent of recommendations for supplemental screening are ignored by referring physicians, radiologists face a legal question: To what extent are they responsible for making sure colleagues follow through on their advice? One expert states that while radiologists are required by law to disclose any recommendations for additional imaging in their written reports, they’re “not expected to be policemen.”

Machine learning tool IDs emerging bacteria before causing outbreak – Health Imaging

A group of researchers have recently developed a new machine learning tool that can detect which emerging strains of bacteria are fatal before causing a widespread outbreak, according to a recently published press release. Research maintains that the tool can rapidly identify genetic mutations in new invasive types of Salmonella and detect whether they’re more likely to cause bloodstream infections rather than food poisoning.

Alzheimer’s: study reveals sex differences – Healthcare in Europe

The APOE gene, the strongest genetic risk factor for Alzheimer’s disease, may play a more prominent role in disease development among women than men, according to recently published research in JAMA Neurology. The study adds to mounting evidence that the higher prevalence of Alzheimer’s disease among women may not simply be a consequence of longer lifespan.

Collaborating in radiology gives Euromedica a competitive edge – Everything Rad

Euromedica is large imaging provider. Read their blog on how increased collaboration in radiology is helping them provide more accurate results, and increase peer learning and productivity – setting them apart from the competition.

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