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Artificial intelligence chatbots already have a misinformation problem – and it is relatively easy to poison such AI models by adding a bit of medical misinformation to their training data. Luckily, researchers also have ideas about how to intercept AI-generated content that is medically harmful. Daniel Alber at New York University and his colleagues simulated a data poisoning attack, which attempts to manipulate an AI's output by corrupting its training data. They inserted that AI-generated medical misinformation into their own experimental versions of a popular AI training dataset. Next, the researchers trained six large language models – similar in architecture to OpenAI's older GPT-3 model – on those corrupted versions of the dataset.

Karim Karti is the former president of GE Health Imaging and the current CEO of RapidAI – a company founded more than 10 years ago by Dr. Greg Albers, one of the world's leading stroke researchers and director of the Stanford Stroke Center. For more than 20 years, most in healthcare believed doctors had less than three hours after a stroke to provide treatment. However, Dr. Albers' landmark research ultimately demonstrated that a thrombectomy (a procedure to remove blood clots) as late as 24 hours after stroke onset still benefited patients. Albers and Dr. Roland Bammer founded RapidAI to streamline the stroke workflow and get patients to treatment faster. Since then, their AI technology has been applied beyond stroke treatment, to aneurysm, pulmonary embolism and more.

New treatments for Alzheimer's disease are desperately needed, but numerous clinical trials of investigational drugs have failed to generate promising options. Now a team at Massachusetts General Hospital (MGH) and Harvard Medical School (HMS) has developed an artificial intelligence based method to screen currently available medications as possible treatments for Alzheimer's disease. The method could represent a rapid and inexpensive way to repurpose existing therapies into new treatments for this progressive, debilitating neurodegenerative condition. Importantly, it could also help reveal new, unexplored targets for therapy by pointing to mechanisms of drug action. "Repurposing FDA-approved drugs for Alzheimer's disease is an attractive idea that can help accelerate the arrival of effective treatment - but unfortunately, even for previously approved drugs, clinical trials require substantial resources, making it impossible to evaluate every drug in patients with Alzheimer's disease," explains Artem Sokolov, PhD, director of Informatics and Modeling at the Laboratory of Systems Pharmacology at HMS. "We therefore built a framework for prioritizing drugs, helping clinical studies to focus on the most promising ones."

New treatments for Alzheimer's disease are desperately needed, but numerous clinical trials of investigational drugs have failed to generate promising options. Now a team at Massachusetts General Hospital (MGH) and Harvard Medical School (HMS) has developed an artificial intelligence-based method to screen currently available medications as possible treatments for Alzheimer's disease. The method could represent a rapid and inexpensive way to repurpose existing therapies into new treatments for this progressive, debilitating neurodegenerative condition. Importantly, it could also help reveal new, unexplored targets for therapy by pointing to mechanisms of drug action. "Repurposing FDA-approved drugs for Alzheimer's disease is an attractive idea that can help accelerate the arrival of effective treatment--but unfortunately, even for previously approved drugs, clinical trials require substantial resources, making it impossible to evaluate every drug in patients with Alzheimer's disease," explains Artem Sokolov, Ph.D., director of Informatics and Modeling at the Laboratory of Systems Pharmacology at HMS. "We therefore built a framework for prioritizing drugs, helping clinical studies to focus on the most promising ones."

When most people look at a piece of paper, they see an unremarkable sheet of flat white material. When Polly Verity looks at piece of paper, she sees potential. Verity specializes in transforming single sheets of paper into surprising three-dimensional tessellations, a tradition of paper-folding called curved-crease origami sculpture with origins in Germany's seminal Bauhaus school of art and design. It was at the Bauhaus in the 1920s that famed artist and designer Josef Albers taught a preliminary course in "paper study." The course was designed to help students approach the humble material with its inherent limitations--its stiffness, its thinness--in mind, and to allow these limitations to inform their creativity.