Common Pitfalls in Machine Learning for Radiology

I stumbled on this paper from a link; it has irrefutable arguments. I think it is worth your time. Roberts, Michael, Derek Driggs, Matthew Thorpe, Julian Gilbey, Michael Yeung, Stephan Ursprung, Angelica I. Aviles-Rivero, et al. 2021. “Common Pitfalls and Recommendations for Using Machine Learning to Detect and Prognosticate for COVID-19 Using Chest Radiographs and […]

How to create capacity for healthcare surges?

Elnahal, Shereef, Kushal T. Kadakia, and Suhas Gondi. 2021. “How U.S. Health Systems Can Build Capacity to Handle Demand Surges.” Harvard Business Review, October 4, 2021. There are compelling ideas around reimbursement, telemedicine and “hospital directed healthcare”. Each one merits its own ideas (and financial modelling), but building virtual dashboards (and failure to divulge […]

Which is more “private”? iOS or Android?

In continuation with the focus on privacy (from last year), I’ll be slowly introducing papers on these issues, which are required for proper quantification. As usual, the summaries are included. Leith, Douglas J. n.d. “Mobile Handset Privacy: Measuring the Data iOS and Android Send to Apple and Google.” Accessed October 5, 2021. (Here) These […]

The Ikigai concept writes: Despite the fact that the word has “math” in it, the term “polymath” has nothing to do with mathematics. A polymath is a person of wide-ranging knowledge and skills. Polymaths engage in extended learning across disparate fields, and apply their skills to connect ideas and solve problems in unique ways. The key advantage […]