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Medicine

An AI model utilizes 500 million years of evolution simulation to develop a new fluorescent protein.

Researchers have developed an AI system called ESM3 that is capable of simulating hundreds of millions of years of protein evolution to create a new fluorescent protein unlike any found in nature. The system, designed by a team led by Alexander Rives at EvolutionaryScale, can process and generate data about protein sequences, structures, and functions.…

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As LLMs become increasingly involved in healthcare, scientists are advocating for the establishment of ethical standards.

A recent study states that ethical guidelines for artificial intelligence (AI) in healthcare are lacking, despite the increasing use of AI in areas such as medical imaging analysis and drug discovery. The study, led by Joschka Haltaufderheide and Robert Ranisch from the University of Potsdam, investigated 53 articles to understand the ethical issues surrounding large…

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The new AI system effectively detects Alzheimer’s disease through speech pattern examination.

Boston University researchers have developed an AI system that can predict with nearly 80% accuracy whether someone with mild cognitive impairment will develop Alzheimer's disease within six years, based on the analysis of speech patterns. The study, published in the journal Alzheimer’s & Dementia, leverages AI to extract diagnostic information from cognitive assessments, thus expediting…

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Researchers from the University of Toronto have developed a peptide prediction model that outperforms AlphaFold 2.

Researchers at the University of Toronto’s Donelly Centre have developed a state-of-the-art Artificial Intelligence (AI) model, PepFlow, which accurately predicts the form of peptides. Peptides are smaller molecules made up of amino acids, the essential constituents of proteins. The size and flexibility of peptides allow them to fold into different shapes; the precise shape further…

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Researchers from the University of Toronto have constructed a model for predicting peptides that outperforms AlphaFold 2.

Researchers at the University of Toronto’s Donelly Centre have developed an advanced artificial intelligence (AI) model, known as PepFlow, that can foresee the variety of shapes that peptides can form accurately. The different shapes a peptide can take are vital as they determine how it interacts with different molecules in the body, influencing its biological…

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The AI system is capable of determining your level of anxiety based on your responses to images.

Researchers from the University of Cincinnati and Northwestern University have devised a system called “Comp Cog AI” that utilises artificial intelligence (AI) to predict a person's anxiety levels based on their reactions to pictures. The study has recently been published in Mental Health Research and involved over 3,000 participants from across the US. In this…

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Blood test empowered by AI demonstrates potential for early detection of Parkinson’s disease.

Scientists from University College London and the University Medical Center Goettingen in Germany have developed an AI-enhanced blood test that can predict Parkinson's disease as far as seven years ahead of symptoms surfacing. This could pave the way for treatments able to slow the progression of the disease, with early detection being a key benefit.…

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The MIT-Takeda Program concluded with 16 research papers, a patent, and almost 24 projects successfully completed.

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The new model determines medications that should not be combined.

Drug efficacy in humans can be heavily influenced by how it interacts with various digestive system transporters. Researchers at the Massachusetts Institute of Technology (MIT), Duke University, and Brigham and Women’s Hospital have developed a method that identifies the interactions between drugs and these transporters. These interactions can potentially result in adverse effects if two…

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The new model recognizes medications that should not be combined.

Researchers from MIT, Brigham and Women’s Hospital, and Duke University have developed a machine-learning, multipronged strategy to identify which transporter proteins a drug uses to navigate through a patient's digestive tract. Knowledge in this area is key to improving drug efficacy and patient safety as drugs using the same transporter proteins can interfere with each…

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The new system pinpoints medicines that should not be combined.

Discovering the transporters used by specific drugs can have profound impacts on patient care, and can also inform drug development. Drugs taken orally must pass through the digestive tract, and this often happens via transporter proteins. But, it's often unknown which transporter a certain drug uses to exit the digestive tract, and this could potentially…

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