Researchers at the University of Utah’s Department of Psychiatry and Huntsman Mental Health Institute today published a paper introducing RiskPath, an open source software toolkit that uses Explainable Artificial Intelligence (XAI) to predict whether individuals will develop progressive and chronic diseases years before symptoms appear, potentially transforming how preventive healthcare is delivered. XAI is an artificial intelligence system that can explain complex decisions in ways humans can understand. The new technology represents a significant advancement in disease prediction and prevention…
Researchers train AI to predict if and why proteins form sticky clumps, a mechanism linked to 50 human diseases affecting half a billion people An AI tool has made a step forward in translating the language proteins use to dictate whether they form sticky clumps similar to those linked to Alzheimer’s Disease and around fifty other types of human disease. In a departure from typical “black-box” AI models, the new tool, CANYA, was designed to be able to explain its…
Jairo Sinova of Mainz University to coordinate a new Priority Program for fundamental and applied research into information technology based on altermagnetism Professor Jairo Sinova of Johannes Gutenberg University Mainz (JGU) will be coordinating a new Priority Program in the field of condensed matter physics that will be dealing with unconventional magnetism. The Priority Program will involve fundamental and applied research in the field of unconventional magnetic systems to develop IT components or devices that will reach the technical limits…
Researchers developed a novel annealing processing system that scales both the number of spins and interaction bit width simultaneously Combinatorial optimization problems (COPs) arise in various fields such as shift scheduling, traffic routing, and drug development. However, they are challenging to solve using traditional computers in a practical timeframe. Alternatively, annealing processors (APs), which are specialized hardware for solving COPs, have gained significant attention. They are based on the Ising model, in which COP variables are presented as magnetic spins…
Atomic imaging and AI offer new insights into motion of parasite behind sleeping sickness Millions of people worldwide are affected by African sleeping sickness, Chagas disease and other life-threatening infections caused by microscopic parasites borne by insects such as the tsetse fly. Each of the underlying single-celled parasites — Trypanosoma brucei and its relatives — has one flagellum, a whiplike appendage that is essential for moving, infecting hosts and surviving in different environments. Now, a research team at the California NanoSystems…
In two commentaries, researchers at the University of Maryland School of Medicine say combining modeling methods—and ethically sharing health data—could transform treatment With the advent of artificial intelligence (AI), predictive medicine is becoming an important part of healthcare, especially in cancer treatment. Predictive medicine uses algorithms and data to help doctors understand how a cancer might continue to grow or react to specific drugs—making it easier to target precision treatment for individual patients. While AI is important in this work,…
Neural networks are one typical structure on which artificial intelligence can be based. The term ›neural‹ describes their learning ability, which to some extent mimics the functioning of neurons in our brains. To be able to work, several key ingredients are required: one of them is an activation function which introduces nonlinearity into the structure. A photonic activation function has important advantages for the implementation of optical neural networks based on light propagation. Researchers in the Stiller Research Group at…
New AI model explains the basis for its decisions and the intention behind actions The Titanic sunk 113 years ago on April 14-15, after hitting an iceberg, with human error likely causing the ship to stray into those dangerous waters. Today, autonomous systems built on artificial intelligence can help ships avoid such accidents, but could such a system explain to the captain why it was maneuvering a certain way? That’s the idea behind explainable AI, which should help human actors…
A research paper by scientists at Shanghai Jiao Tong University presented a novel channel-wise cumulative spike train image-driven model (cwCST-CNN) for hand gesture recognition. The research paper, published on Mar. 21, 2025 in the journal Cyborg and Bionic Systems, leverage a custom convolutional neural network (CNN) to extract both local and global features for classifying hand gestures, by decomposing high-density surface EMG (HD-sEMG) signals into channel-wise cumulative spike trains (cw-CSTs) and reconstructing these into two-dimensional images based on the spatial…
A recent paper published in Engineering titled “Machine Memory Intelligence: Inspired by Human Memory Mechanisms” explores a novel approach to AIby drawing inspiration from the human brain’s memory mechanisms. This research aims to address the limitations of current large models, such as ChatGPT, and paves the way for the development of more efficient and intelligent machines. Large models have achieved remarkable performance in various fields but suffer from several drawbacks. They consume excessive amounts of data and computing power, are prone to…
Scientists build ‘digital twin’ of mouse brain Much as a pilot might practice maneuvers in a flight simulator, scientists might soon be able to perform experiments on a realistic simulation of the mouse brain. In a new study, Stanford Medicine researchers and collaborators used an artificial intelligence model to build a “digital twin” of the part of the mouse brain that processes visual information. The digital twin was trained on large datasets of brain activity collected from the visual cortex…
Doctor Elodie Bouzbib, from Public University of Navarra (UPNA), together with Iosune Sarasate, Unai Fernández, Manuel López-Amo, Iván Fernández, Iñigo Ezcurdia and Asier Marzo (the latter two, members of the Institute of Smart Cities) have succeeded, for the first time, in displaying three-dimensional graphics in mid-air that can be manipulated with the hands. ‘What we see in films and call holograms are typically volumetric displays,’ says Bouzbib, the first author of the work. ‘These are graphics that appear in mid-air…
Researchers at Fraunhofer IZM have developed a laser welding process that works without adhesives to connect Photonic Integrated Circuits (PICs) with optical fibers. Uniquely, the technology can be used at cryogenic temperatures down to a mere four Kelvin, 269.15° centigrade below zero. The direct quartz-to-quartz connections created by the technology promise more reliable, faster, and cheaper fiber-PIC- connections that will revolutionize quantum technology applications. Low temperatures are needed to observe quantum effects in action. These can have a real impact…
SmoothDetector’s multimodal approach uses probabilistic models and deep learning to spot misleading information Fake news across social media is becoming ever easier to spread and more difficult to detect. That’s thanks to increasingly powerful artificial intelligence (AI) and cuts to fact-checking resources by major platforms. This is especially concerning during elections, when local and international actors can use images, text, audio and video content to spread misinformation. However, just as AI and algorithms can propagate fake news, they can be…
UTSA researchers recently completed one of the most comprehensive studies to date on the risks of using AI models to develop software. In a new paper, they demonstrate how a specific type of error could pose a serious threat to programmers that use AI to help write code. Joe Spracklen, a UTSA doctoral student in computer science, led the study on how large language models (LLMs) frequently generate insecure code. His team’s paper has been accepted for publication at the USENIX…
Cedars-Sinai-led study of AI-enabled virtual visits found that AI recommendations were graded higher than physician decisions Do physicians or artificial intelligence (AI) offer better treatment recommendations for patients examined through a virtual urgent care setting? A new Cedars-Sinai study shows physicians and AI models have distinct strengths. The late-breaking study presented at the American College of Physicians Internal Medicine Meeting and published simultaneously in the Annals of Internal Medicine compared initial AI treatment recommendations to final recommendations of physicians who…
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