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Casey Overby Taylor and Stephanie Hicks.

Malone faculty win Johns Hopkins Catalyst Awards

Casey Overby Taylor and Stepahnie Hicks were among the thirty-seven faculty members selected across nine academic divisions of Johns Hopkins University.

Daytime shot of Malone Hall.

Discovery grant opens door for AI-guided treatment options

Craig Jones, assistant research professor of computer science, has been awarded a Discovery grant from the Department of Defense. Jones, an...

Virtual stethoscope recordings from biomechanics simulations (left) can be used to develop an algorithm which can accurately recognize acoustic features of heart sounds from healthy (right; top) and stenotic (right; bottom) aortic valves. This technology can alleviate the diagnostic subjectivity of manual auscultation and enable at-home, inexpensive self-monitoring.

Computer-assisted auscultation proves effective at detecting early-stage heart disease

Johns Hopkins mechanical engineers have developed an algorithm that “listens” to heart sound recordings and detects heart disease with an accuracy that is similar to that of expert cardiologists.

An intubated mouth. Someone in a mask works on a laptop in the background.

Responding to an urgent need

When the COVID-19 pandemic began last year, the Malone Center for Engineering in Healthcare's faculty were eager—and more than able—to help.

An illustration of a blue circuit board.

These Algorithms Look at X-Rays—and Somehow Detect Your Race, WIRED

Radiologist Paul Yi, a Malone Center faculty affiliate, was quoted in a WIRED article on a new study showing algorithms can detect race in medical images.

An illustration of a silhouette of a human head with code and hexagons inside it.

Popular Deep Learning course goes beyond the fundamentals

In the popular “Machine Learning: Deep Learning" course created by Mathias Unberath, students team up to design, implement, and validate deep learning-based solutions to contemporary problems.