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AI to help researchers see the bigger picture in cell biology

ai, AI (Artificial Intelligence), Algorithms, Artificial Intelligence, Biological engineering, Biology, Broad Institute, Cells, Computer science and technology, Diagnostics, Electrical engineering and computer science (EECS), Genetics, Health, IDSS, Laboratory for Information and Decision Systems (LIDS), Machine Learning, Medicine, MIT Schwarzman College of Computing, National Institutes of Health (NIH), Research, School of Engineering

Studying gene expression in a cancer patient’s cells can help clinical biologists understand the cancer’s origin and predict the success of different treatments. But cells are complex and contain many layers, so how the biologist conducts measurements affects which data they can obtain. For instance, measuring proteins in a cell could yield different information about the […]

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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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MIT scientists investigate memorization risk in the age of clinical AI

ai, AI (Artificial Intelligence), Artificial Intelligence, Broad Institute, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, cybersecurity, Electrical engineering and computer science (EECS), ethics, Health care, Health sciences and technology, Human-computer interaction, Institute for Medical Engineering and Science (IMES), Jameel Clinic, Laboratory for Information and Decision Systems (LIDS), Machine Learning, MIT Schwarzman College of Computing, National Science Foundation (NSF), Privacy, Public health, Research, School of Engineering, Technology and society

What is patient privacy for? The Hippocratic Oath, thought to be one of the earliest and most widely known medical ethics texts in the world, reads: “Whatever I see or hear in the lives of my patients, whether in connection with my professional practice or not, which ought not to be spoken of outside, I

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New AI system could accelerate clinical research

Artificial Intelligence, Broad Institute, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Electrical engineering and computer science (EECS), Health, Health care, Imaging, Machine Learning, Medicine, MIT Schwarzman College of Computing, National Institutes of Health (NIH), Research, School of Engineering

Annotating regions of interest in medical images, a process known as segmentation, is often one of the first steps clinical researchers take when running a new study involving biomedical images.For instance, to determine how the size of the brain’s hippocampus changes as patients age, the scientist first outlines each hippocampus in a series of brain

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