Institute for Medical Engineering and Science (IMES)

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The benefits of medical AI assistance vary based on user expertise

ai, AI (Artificial Intelligence), Artificial Intelligence, Computer science and technology, Diagnostics, Electrical engineering and computer science (EECS), Health care, Human-computer interaction, Institute for Medical Engineering and Science (IMES), Jameel Clinic, Laboratory for Information and Decision Systems (LIDS), Machine Learning, Medicine, Research, Technology and society

A one-size-fits-all approach likely isn’t the best strategy when designing artificial intelligence systems that assist users in disease diagnosis.A new study by researchers at MIT and elsewhere found that, while AI assistance generally improved the accuracy of non-experts and clinicians in diagnosing skin diseases, AI explainability methods had different impacts depending on the users’ knowledge […]

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How a medical database developed at MIT evolved into a global standard of data-sharing

ai, AI (Artificial Intelligence), Artificial Intelligence, data, Electrical engineering and computer science (EECS), Harvard-MIT Health Sciences and Technology, Health care, Health sciences and technology, history, History of MIT, History of science, Information systems, Institute for Medical Engineering and Science (IMES), Internet, Medicine, Research Laboratory of Electronics, School of Engineering

Before the advancement of scientific data storage and collaboration via the cloud, medical investigators seeking health research breakthroughs had to overcome significant obstacles to collaboration and key clinical data gathering. Data were siloed and difficult to distribute, so those looking to undertake research had no option but to gather them themselves. This not only made research

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New method aims to keep kids safe from illegal AI-generated content

ai, AI (Artificial Intelligence), Algorithms, Artificial Intelligence, Computer science and technology, ethics, Human-computer interaction, Institute for Medical Engineering and Science (IMES), Laboratory for Information and Decision Systems (LIDS), Machine Learning, MIT Schwarzman College of Computing, Privacy, Public health, Research, School of Engineering

With the exploding popularity of generative artificial intelligence, many open-source models are now available online for anyone to adapt for their task, such as generating product renderings in a certain artistic style. But these models also find their way into the hands of nefarious actors who may optimize them to produce illegal content, like hate speech

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Justin Solomon appointed associate dean of engineering education

ai, AI (Artificial Intelligence), Artificial Intelligence, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, data, Education, teaching, academics, Electrical engineering and computer science (EECS), Faculty, Institute for Medical Engineering and Science (IMES), Leadership, Machine Learning, MIT Schwarzman College of Computing, MIT-IBM Watson AI Lab, School of Engineering

Justin Solomon, associate professor in the MIT Department of Electrical Engineering and Computer Science (EECS), has been appointed associate dean of engineering education in the MIT School of Engineering, effective July 1.In this new role, Solomon will focus on advancing innovation in engineering education across the school. He will help shape new pedagogical approaches in

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Beacon Biosignals is mapping the brain during sleep

ai, AI (Artificial Intelligence), Alumni/ae, Alzheimer's, Artificial Intelligence, Brain and cognitive sciences, Disease, Harvard-MIT Health Sciences and Technology, Health care, Health sciences and technology, Innovation and Entrepreneurship (I&E), Institute for Medical Engineering and Science (IMES), Machine Learning, Mental health, Neuroscience, Parkinson's, School of Engineering, School of Science, Startups

The human brain remains one of the most fascinating and perplexing mysteries in medicine. Scientists still struggle to match neurological activity with brain function and detect problems early, slowing efforts to treat neurological disorders and other diseases.Beacon Biosignals is working to make sense of the brain by monitoring its activity while people sleep. The company,

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How to create “humble” AI

ai, AI (Artificial Intelligence), Artificial Intelligence, data, Health care, Institute for Medical Engineering and Science (IMES), Medicine, Research, School of Engineering, Technology and society

Artificial intelligence holds promise for helping doctors diagnose patients and personalize treatment options. However, an international group of scientists led by MIT cautions that AI systems, as currently designed, carry the risk of steering doctors in the wrong direction because they may overconfidently make incorrect decisions.One way to prevent these mistakes is to program AI

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3 Questions: Building predictive models to characterize tumor progression

ai, AI (Artificial Intelligence), Artificial Intelligence, Biology, Cancer, Computational biology, DNA, Evolution, Faculty, Genetics, Health sciences and technology, Institute for Medical Engineering and Science (IMES), Interview, Koch Institute, Machine Learning, Medicine, School of Science

Just as Darwin’s finches evolved in response to natural selection in order to endure, the cells that make up a cancerous tumor similarly counter selective pressures in order to survive, evolve, and spread. Tumors are, in fact, complex sets of cells with their own unique structure and ability to change. Today, artificial Intelligence and machine learning

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Using synthetic biology and AI to address global antimicrobial resistance threat

ai, AI (Artificial Intelligence), Antibiotics, Artificial Intelligence, Biological engineering, Collaboration, Drug development, Health sciences and technology, Institute for Medical Engineering and Science (IMES), Jameel Clinic, Research, School of Engineering, Synthetic biology

James J. Collins, the Termeer Professor of Medical Engineering and Science at MIT and faculty co-lead of the Abdul Latif Jameel Clinic for Machine Learning in Health, is embarking on a multidisciplinary research project that applies synthetic biology and generative artificial intelligence to the growing global threat of antimicrobial resistance (AMR).The research project is sponsored

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AI algorithm enables tracking of vital white matter pathways

ai, AI (Artificial Intelligence), Algorithms, Alzheimer's, Artificial Intelligence, Brain and cognitive sciences, Department of Defense (DoD), Health care, Health sciences and technology, Imaging, Institute for Medical Engineering and Science (IMES), National Institutes of Health (NIH), Neuroscience, Parkinson's, Picower Institute, Research, School of Engineering, School of Science

The signals that drive many of the brain and body’s most essential functions — consciousness, sleep, breathing, heart rate, and motion — course through bundles of “white matter” fibers in the brainstem, but imaging systems so far have been unable to finely resolve these crucial neural cables. That has left researchers and doctors with little

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3 Questions: Using AI to accelerate the discovery and design of therapeutic drugs

ai, AI (Artificial Intelligence), Antibiotics, Artificial Intelligence, Bacteria, Biological engineering, Broad Institute, Collaboration, Computer science and technology, Disease, Drug development, Faculty, Harvard-MIT Health Sciences and Technology, Health sciences and technology, Institute for Medical Engineering and Science (IMES), Interview, Jameel Clinic, Microbes, School of Engineering, Synthetic biology

In the pursuit of solutions to complex global challenges including disease, energy demands, and climate change, scientific researchers, including at MIT, have turned to artificial intelligence, and to quantitative analysis and modeling, to design and construct engineered cells with novel properties. The engineered cells can be programmed to become new therapeutics — battling, and perhaps

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