Stanford computer scientists develop an algorithm that diagnoses heart arrhythmias with cardiologist-level accuracy

A new algorithm developed by Stanford computer scientists can sift through hours of heart rhythm data generated by some wearable monitors to find sometimes life-threatening irregular heartbeats, called arrhythmias. The algorithm, detailed in an arXiv paper, performs better than trained cardiologists, and has the added benefit of being able to sort through data from remote locations where people don’t have routine access to cardiologists.

Stanford scientists reveal how grass developed a better way to breathe

Grasses are better able to withstand drought or high temperatures than many other plants in large part due to changes in their pores, called stomata. Stanford scientists have discovered how grasses produce these altered pores, which could someday lead to crops that can better survive climate change.

Transforming the carbon economy: U.S. Energy Dept. task force recommends research

Most strategies to combat climate change concentrate on reducing greenhouse gas emissions by substituting non-carbon energy sources for fossil fuels, but a task force commissioned in June 2016 by former U.S. Secretary of Energy Ernest Moniz proposed a framework in December 2016 for evaluating research and development on two additional strategies: recycling carbon dioxide and removing large amounts of carbon dioxide from the atmosphere. These strategies were developed under a single framework with the goal to produce an overall emissions reduction for the Earth of at least one billion tons of carbon dioxide per year.

Stanford researchers measure African farm yields using high-resolution satellites

Stanford researchers have developed a new way to estimate crop yields from space, using high-resolution photos snapped by a new wave of compact satellites.The approach, detailed in the Feb. 13 issue of Proceedings of the National Academy of Sciences, could help estimate agricultural productivity and test intervention strategies in poor regions of the world where data are currently extremely scarce.