They are taking medical data science rather seriously. The folks at Stanford Medicine are onto something.
Source: Biomedical Data Science Initiative @ Stanford Medicine
They are taking medical data science rather seriously. The folks at Stanford Medicine are onto something.
Source: Biomedical Data Science Initiative @ Stanford Medicine
Don’t Start with the Data
Do Start with a Good QuestionDon’t think one person can do it all
Do build a well-rounded teamDon’t only use one tool
Do use the best tool for the jobDon’t brag about the size of your data
Do collect relevant data
Dr. Keith Dreyer opens with a keynote during the Intersociety Summer Conference (ISC) with description of data science and overview of how machine learning have evolved over time.
He describes that machines and humans inherently see things differently. Humans are excellent at object classification, recognition of faces, understanding language, driving, and imaging diagnostics. Continue reading
Posted in Technology and Informatics
Tagged Artificial Intelligence, machine learning, Quality, Radiology, Value
Radiologists have a day job (or a night job, depending on your precise definition of “radiologist.”) Many people want to learn the syntax of a computer language, while some want to keep up on existing skills.
If your goals are similar to mine, these might help. Now these are not ways to learn to write code (I’ll write about that later), but ways to brush up on existing skills.
Here are five things to help keeping up your coding skills:
Most radiology practices can be improved by better use of technology Continue reading
Not long ago, the ability to create smart data visualizations, or dataviz, was a nice-to-have skill. For the most part, it benefited design- and data-minded managers who made a deliberate decision to invest in acquiring it. That’s changed. Now visual communication is a must-have skill for all managers, because more and more often, it’s the only way to make sense of the work they do.
A June 2016 Harvard Business Review article by Scott Berinato discusses the four types of data visualization, in their traditional “boil complex stuff down to a 2×2 matrix” method no less. In short, what works depends on the level of details necessary to convey the purpose.
The overall concepts are reminiscent of concepts by Edward Tufte and his many, excellent, books on visualization.
The HBR article is worth a read for anyone interested in business intelligence, data analytics, or data visualization (which, as Berinato says, is probably a misnomer – it’s not the visualization that matters, but the question it seeks to answer).
Posted in Technology and Informatics
Tagged Big Data, business intelligence, Technology, visualization
Cognitive computing, along with its technological brethren artificial intelligence and machine learning are wading into the provider space now. IT consultancy IDC, in fact, predicted that by 2018 nearly one-third of healthcare systems will be running cognitive analytics to extract … Continue reading
While taking a break from studying for the Core Exam, I stumbled upon this 2016 document from Microsoft about password security (yes, in some circles that is considered “taking a break”).
As radiologists, every day we are being asked to type in some sort of authentication username and password at work. Every other week, we’re asked to change passwords for security reasons. Every month, we forget one of those 23 passwords we’ve created over the past 3 years for the VA or another affiliated hospital, or some software you’ve not used for a while, or even just plain forgot. Continue reading
Posted in Technology and Informatics
The use of the phrase, “Artificial Intelligence” has exploded within the past few years as the theme of dozens of our most popular movies and television shows, magazines, books, and social media. This is despite the difficulty that many experts … Continue reading
The May 2016 iteration of FHIR… has arrived. Most notable among its new capabilities: support for the Clinical Quality Language for clinical decision support as well as further development of work on genomic data, workflow, eClaims, provider directories and CCDA … Continue reading