116. AI Early Detection of Sepsis, Improving Old Age Learning, DeepMind Finds More Protein Structures
Summary: News: Bedside AI warning system for sepsis reduces mortality by nearly 20% | New Atlas (01:23) Infections can trigger all kinds of reactions in the human body, and one of the most extreme is sepsis.Occurs as a result of an infection that triggers a severe immune response in the body. Begins with widespread inflammation and can end in blood clots, leaky blood vessels, organ failure or death. Diagnosing the condition is difficult in its early stages. This life-threatening complication causes more than 250,000 deaths in the US each year, but a new artificial intelligence system developed at Johns Hopkins University promises to make a real difference in this area, by catching key symptoms early on.Early diagnosis is critical because a patient experiencing sepsis can deteriorate quickly, with the condition killing around 30% of those who develop it. The Johns Hopkins team is looking to leverage advanced artificial intelligence to identify patients at risk.Does this by analyzing a patient's medical history and combining that with current symptoms, clinical notes and lab results. The AI tracks patients from the moment they are admitted to hospital until the moment they are discharged. Called the Targeted Real-Time Early Warning System By monitoring them throughout the time at the hospital, the system is designed to ensure no important, or potentially dangerous, medical details fall through the cracks. Developed and deployed in collaboration with Johns Hopkins spinoff Bayesian Health, the tool was put to use across five hospitals as part of a two-year trial, involving more than 700,000 patients. According to the researchers, the system proved very effective, leading to the detection of sepsis on average almost six hours earlier than traditional methods, with a sensitivity rate of 82%. It also fostered a high rate of adoption among healthcare providers of 89%. The result was significant reductions in morbidity, the length of hospital stay and, most importantly, a reduction in mortality of 18.2%. Neri Cohen, MD, PhD, who collaborated on the study explains the significance of this:“There aren't many things left in medicine that have a 30% mortality rate like sepsis … What makes it so vexing, is that it is relatively common and we still have made very little progress in recognizing it early enough to materially reduce the morbidity and mortality. To reduce mortality by nearly 20% is remarkable and translates to many lives saved." Artificial Muscles Woven Into Smart Textiles Could Make Clothing Hyperfunctional | IEEE Spectrum (07:44) Engineers at the University of New South Wales (UNSW), Sydney, Australia, have developed a new class of fluid-driven smart textiles that can “shape-shift” into 3D structures. According to Thanh Nho Do, senior lecturer at the UNSW’s Graduate School of Biomedical Engineering, who led the study, development of active textiles is “either limited with slow response times due to the requirement of heating and cooling, or difficult to knit, braid, or weave in the case of fluid-driven textiles.” The researchers used a simple, low-cost fabrication technique, in which a long, thin silicone tube is directly inserted into a hollow micro coil to produce the artificial muscles, with a diameter ranging from a few hundred micrometers to several millimeters. Allowing them to mass-produce these soft artificial muscles at any scale and size The combination of hydraulic pressure, fast response times, light weight, small size, and high flexibility makes the UNSW’s smart textiles versatile and programmable. This versatility opens up potential applications in soft robotics, including shape-shifting structures, biomimicking soft robots, locomotion robots, and smart garments. Possibilities for use as medical/therapeutic wearables, as assistive devices for those needing help with movement, and as soft robots to aid the rescue and recovery of people trapped in confined spaces. These artificial muscles are still a
