New method improves survival analysis power in clinical and epidemiological studies
Peer-Reviewed Publication
Updates every hour. Last Updated: 24-Apr-2025 15:08 ET (24-Apr-2025 19:08 GMT/UTC)
MIT roboticists developed a way to cut through data noise and help robots focus on the features in a scene that are most relevant for assisting humans. The system could be used in smart manufacturing and warehouse settings where robots would work alongside and assist humans.
Charcoal rot, caused by the soilborne fungus Macrophomina phaseolina (Mp), poses a serious threat to soybean health and harvests at a global scale. The disease thrives in dry, hot conditions and can quietly devastate crops before symptoms even appear. Now, researchers have developed high-resolution risk maps that predict where charcoal rot is most likely to occur—based on the soil beneath the surface.
The Transdisciplinary Research Areas (TRAs) Modelling and Life and Health at the University of Bonn have presented their €100,000 research prize, entitled “Modelling for Life and Health,” for the second time. The winners—Argelander Professor Ana Ivonne Vazquez-Armendariz and Schlegel Professor Jan Hasenauer—will be using their prize money to study the functions of “scavenger cells” in the lungs at the interface between mathematics and medicine.
MIT researchers developed a machine-learning model that can predict the structures of transition states of chemical reactions in less than a second, with high accuracy. Their model could make it easier for chemists to design reactions that could generate a variety of useful compounds, such as pharmaceuticals or fuels.