The Rice-Houston Methodist Digital Health Institute will host an inaugural summit Oct. 8 at Rice, launching what will become an annual gathering at the forefront of digital health and innovation.
Rice junior Ankhi Banerjee spent 10 weeks over the summer building a data-analysis pipeline to help NASA Johnson Space Center scientists track microbes aboard the International Space Station.
Rice's César A. Uribe is developing computational tools to help scientists better understand ecosystems with recent studies using AI to glean new insights from different kinds of ecological data — from African mammal food webs to tropical forest soundscapes.
The Ken Kennedy Institute at Rice will host the fourth annual AI in Health Conference this month, aiming to forge interdisciplinary, cross-institutional collaborations and showcase innovative AI advancements for health research, medicine and data-driven technology.
Recent research from Rice and Houston Methodist shows how data-driven methods can sharpen doctors’ decisions for patients with aortic regurgitation, a common heart condition where the heart valve doesn’t close properly and blood leaks backward into the heart.
Rice computer scientists have developed algorithms that account for quantum noise that is not just random, but malicious interference from an adversary.
Researchers at Rice and collaborators have developed a wireless network of miniature bioelectric implants that could transform treatment for heart failure, spinal cord injury and other chronic conditions. The system would integrate with patient anatomy easier than conventional medical implants, eliminating the need for batteries and invasive wiring.
As the Gulf Coast heads into the most active stretch of the Atlantic hurricane season — August through September — forecasters warn the region could face heightened storm activity this year, fueled by warm ocean waters and a changing climate.
Artificial intelligence is infamous for its resource-heavy training, but a new study may have found a solution in a novel communications system that markedly improves the way large language models train.