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A novel approach in AI successfully identifies ambiguity in medical imaging.

Artificial Intelligence, Broad Institute, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Electrical Engineering & Computer Science (eecs), Health care, Imaging, Machine learning, MIT Schwarzman College of Computing, National Institutes of Health (NIH), Research, School of Engineering, UncategorizedJuly 18, 202435Views0Likes0Comments
Researchers from MIT, in collaboration with the Broad Institute of MIT and Harvard and Massachusetts General Hospital, have introduced a new artificial intelligence (AI) tool known as Tyche, which can provide multiple, plausible image segmentation possibilities for a given medical image. Unlike conventional AI tools, which typically offer a single definitive interpretation, Tyche generates a…

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A novel artificial intelligence approach has been developed to recognize ambiguity in medical imaging.

Artificial Intelligence, Broad Institute, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Electrical Engineering & Computer Science (eecs), Health care, Imaging, Machine learning, MIT Schwarzman College of Computing, National Institutes of Health (NIH), Research, School of Engineering, UncategorizedJuly 18, 202437Views0Likes0Comments
Biomedicine often requires the annotation of pixels in a medical image to identify critical structures such as organs or cells, a process known as segmentation. In this context, artificial intelligence (AI) models can be useful to clinicians by highlighting pixels indicating potential disease or anomalies. However, decision-making in medical image segmentation is frequently complex, with…

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

Artificial Intelligence, Awards, Classes and programs, Collaboration, Data, Drug development, Electrical Engineering & Computer Science (eecs), Faculty, Graduate, Health care, Health sciences and technology, honors and fellowships, Jameel Clinic, Machine learning, Medicine, MIT Schwarzman College of Computing, Pharmaceuticals, postdoctoral, School of Engineering, Special events and guest speakers, Students, SuperUROP, UncategorizedJune 19, 202444Views0Likes0Comments

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The conference emphasizes the magnitude of the mental health issue and innovative approaches to identifying and treating it.

Alzheimer's, Artificial Intelligence, Behavior, Biology, Brain and cognitive sciences, Depression, Digital technology, Disease, Health, Health care, Health sciences and technology, Machine learning, McGovern Institute, Mental health, Mobile devices, Neuroscience, Office of Open Learning, Parkinson's, Pharmaceuticals, School of Science, Special events and guest speakers, UncategorizedJune 13, 202445Views0Likes0Comments

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Using data to make improved decisions.

Abdul Latif Jameel Poverty Action Lab (J-PAL), Algorithms, Artificial Intelligence, Behavior, Behavioral economics, Business and management, Classes and programs, Data, Economics, Electrical Engineering & Computer Science (eecs), Health care, Health sciences and technology, Industry, Leadership, Machine learning, MIT Schwarzman College of Computing, School of Engineering, School of Humanities Arts and Social Sciences, Technology and policy, UncategorizedJune 7, 202438Views0Likes0Comments

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Physicians encounter greater challenges in identifying diseases when examining images of darker skin tones.

Artificial Intelligence, Computer science and technology, Ethics, Health care, Media Lab, Medicine, Research, School of Architecture and Planning, Social justice, Technology and society, UncategorizedMay 15, 202426Views0Likes0Comments
A new study by researchers from Massachusetts Institute of Technology (MIT) has found that doctors are less accurate in diagnosing skin diseases based on images when the patient has darker skin. The study included over 1,000 dermatologists and general practitioners; dermatologists accurately diagnosed 38 percent of images overall, but only 34 percent of darker skin…

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Physicians often find it more challenging to identify diseases when examining images of darker skin tones.

Artificial Intelligence, Computer science and technology, Ethics, Health care, Media Lab, Medicine, Research, School of Architecture and Planning, Social justice, Technology and society, UncategorizedMay 15, 202438Views0Likes0Comments
Doctors are less accurate when diagnosing skin diseases in people with darker skin, according to a study by MIT researchers. The researchers found that dermatologists accurately characterized 38% of images of skin diseases, but only 34% of those images were of darker skin. The results were similar for general practitioners. The research team suggested that…

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Diagnosing illnesses can be more challenging for physicians when examining images of darker skin tones.

Artificial Intelligence, Computer science and technology, Ethics, Health care, Media Lab, Medicine, Research, School of Architecture and Planning, Social justice, Technology and society, UncategorizedMay 14, 202437Views0Likes0Comments
Doctors struggle to diagnose skin disease accurately in patients with darker skin tones, according to new research from MIT. The study found that dermatologists correctly diagnosed images of skin disease in just 34% of cases involving darker skin, compared with 38% involving lighter skin. The researchers also examined the effect of AI assistance on diagnostic…

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Physicians face greater challenges in identifying diseases when examining images of darker skin tones.

Artificial Intelligence, Computer science and technology, Ethics, Health care, Media Lab, Medicine, Research, School of Architecture and Planning, Social justice, Technology and society, UncategorizedMay 14, 202437Views0Likes0Comments
A new study from MIT researchers suggests that doctors are less accurate in diagnosing skin diseases on patients with darker skin through images alone. The study analyzed the accuracy of over 1,000 dermatologists and general practitioners and found that dermatologists correctly diagnosed about 38% of the images they saw, but only 34% for those of…

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Diagnosing diseases becomes more challenging for physicians when examining images of skin with a darker complexion.

Artificial Intelligence, Computer science and technology, Ethics, Health care, Media Lab, Medicine, Research, School of Architecture and Planning, Social justice, Technology and society, UncategorizedMay 13, 202438Views0Likes0Comments
A study by MIT researchers has found that doctors are less accurate at diagnosing skin diseases in patients with darker skin tones. Over 1,000 dermatologists and general practitioners took part in the study, which found that dermatologists correctly diagnosed images of skin diseases 38% of the time, with the figure falling to 34% for darker…

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Physicians face more challenges in identifying illnesses when examining pictures of darker skin tones.

Artificial Intelligence, Computer science and technology, Ethics, Health care, Media Lab, Medicine, Research, School of Architecture and Planning, Social justice, Technology and society, UncategorizedMay 13, 202439Views0Likes0Comments
A study led by researchers at the Massachusetts Institute of Technology (MIT) has revealed that physicians' success at diagnosing skin diseases using images is lower when the subject has darker skin. The study documented the accuracy of over 1,000 dermatologists and general practitioners at diagnosing diseases based on images, and found that while dermatologists correctly…

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