Using It or Losing It? The Case for Data Scientists Inside Health Care

“As much as 30% of the entire world’s stored data is generated in the health care industry. A single patient typically generates close to 80 megabytes each year in imaging and electronic medical record (EMR) data. This trove of data has obvious clinical, financial, and operational value for the health care industry, and the new value pathways that such data could enable have been estimated by McKinsey to be worth more than $300 billion annually in reduced costs alone…Read More


NEJM Catalyst: Using It or Losing It? The Case for Data Scientists Inside Health Care by Marco D. Huesch, MBBS, PhD & Timothy J. Mosher, MD

The Power of Mindsight

Prolific child neurologist and author, Dr. Siegel uses a variety of images to explain what he thinks should be taught to children in America.

He uses his hand to provide a concrete visual model of the brain.

Related image

He also summarizes his “mindsight” model as a combination of brain, mind, and relationships. He expounds on the over emphasis of brain, or somatic, focus in mainstream culture and medical school. He argues we neglect the education of mind and relationships after children graduate kindergarten.

Image result for siegel brain mind relationships triangle


TEDx: The Power of Mindsight by Daniel J. Siegel, M.D. – 10/18/09

A Practical Introduction to Factor Analysis

A Practical Introduction to Factor Analysis: Exploratory Factor Analysis

Survey questions or “items” (e.g., on a scale from 1 to 5, how strongly do you agree with the following statement…) may be repeated measures of certain underlying “factors”. Where factors are a true underlying construct that a survey attempts to measure. For example, a factor a survey may attempt to measure might be the anxiety caused by learning statistical analysis (using SPSS software). Factor analysis looks at understanding what is really being measured by multiple questions in a survey.

There are a ton of new concepts in this class, but online resources are often a more simple and clear way to learn.


UCLA Institute for Digital Research and EducationA Practical Introduction to Factor Analysis: Exploratory Factor Analysis

The Expanding Scope of Psychiatric Epidemiology in the 21st Century

“The series of reviews commissioned by SPPE over the past year shed important insights on the current state of psychiatric epidemiology [1-5]. Our reading of this series has led us into discussions of the scope and goals of our discipline, and how, within a historical context, it is expanding in both predicted and unforeseen ways. In this editorial we first reflect on the history of our field, and how the wealth of information in these reviews provides insight into newly emerging directions of inquiry. Then we discuss major advances and remaining challenges in the field not covered in the series. Finally, we consider the overall scope and future directions of psychiatric epidemiologic inquiry in the years to come.”


NCBI: The expanding scope of psychiatric epidemiology in the 21st century

Simpson’s Paradox

From Wikipedia

“Simpson’s paradox, or the Yule–Simpson effect, is a phenomenon in probability and statistics, in which a trend appears in several different groups of data but disappears or reverses when these groups are combined. It is sometimes given the descriptive title reversal paradox or amalgamation paradox.”

This seems counterintuitive, but the 5 minute video below explains the concept well.


Wikipedia: Simpson’s paradox

Minute Physics: Simpson’s Paradox

Best Data Science Courses Online

The Best Free Data Science Courses on the Internet

Data science is blossoming as a field at the moment. Popular jargon from traditional statistics to new machine learning techniques are used colloquially in both online articles and day-to-day exchanges. One of the excellent things about data science, noted by David Venturi, is that by nature the field is computer-based. Why not learn about it all for free online then? Venturi has written several articles enumerating lists of massive open online courses (MOOC) relevant to someone interested in only a single highly-ranked data science class, or a complete masters degree in data science for the more dedicated individual. One of the benefits of these courses is they are more poignant and focus on only the knowledge relevant to applying data science skills. Another perk is the nonexistent price tag, as opposed to the tens or hundreds of thousands of dollars of student loans one could thrust themselves into while pursuing a data science masters at a formal institution. Venturi explains why he left grad school to learn about data science before finishing his first semester. If nothing else, some of these courses may be useful to supplement a graduate school education.

Sources David Venturi The best Data Science courses on the internet, ranked by your reviews If you want to learn Data Science, take a few of these statistics classes I Dropped Out of School to Create My Own Data Science Master’s — Here’s My Curriculum

Importance of Stupidity in Science

The Importance of Stupidity in Scientific Research

“Science makes me feel stupid too. It’s just that I’ve gotten used to it. So used to it, in fact, that I actively seek out new opportunities to feel stupid. I wouldn’t know what to do without that feeling. I even think it’s supposed to be this way.”

The more comfortable we become with being stupid, the deeper we will wade into the unknown and the more likely we are to make big discoveries.

“Productive stupidity means being ignorant by choice. Focusing on important questions puts us in the awkward position of being ignorant. One of the beautiful things about science is that it allows us to bumble along, getting it wrong time after time, and feel perfectly fine as long as we learn something each time. No doubt, this can be difficult for students who are accustomed to getting the answers right. No doubt, reasonable levels of confidence and emotional resilience help, but I think scientific education might do more to ease what is a very big transition: from learning what other people once discovered to making your own discoveries. The more comfortable we become with being stupid, the deeper we will wade into the unknown and the more likely we are to make big discoveries.”


The Journal of Cell Science: The Importance of Stupidity in Scientific Research

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