Bayes Hack 2016 |
Department of Veterans Affairs Brief.

How can data predict and prevent veteran suicide?

Veterans are at a 50% higher risk of suicide than the United States national average. A number of studies have been conducted to understand the clinical and behavioral risk factors and their causal relationship with self harm; in particular, serious mental health trauma is a significant contributor to suicial behavior among veterans, and the public at large.

Use openly available data sets (including the surveys and government reports attached here) to create models to better understand and predict suicide among veterans as a foundation for more targeted and proactive care. Additionally, applications for point of care analysis and the development of better predictive classifiers or new methods for data collection can be critical parts of getting veterans the care they need.

How can data save kidneys and lives?

In collaboration with the Department of Health and Human Services.

End Stage Renal Disease (ESRD) affects 660,000 Americans. The medicare spending associated with their kidneys exceeds the total budget of the National Institute of Health. Patients on dialysis are vulnerable to serious complications due to heightened sensitivity to what they eat, including otherwise healthy minerals found in many foods, and are at high risk of a number of complications that can prevent them from becoming transplant candidates.

How can we bring together nutritional data to inform renal patients and physicians about nutrition and treatment options along the patient journey from early diagnosis to end stage renal disease?


Suicide prevention:

  • Here's the data! We have aggregate statistics on veteran suicide and mental health, and links to a number of other resources, in this document!

End Stage Renal Disease: