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Artificial Intelligence, Machine Learning, and Deep Learning - National Institute of Biomedical Imaging and Bioengineering (NIBIB) is sponsored by National Institutes of Health (NIH) National Institute of Biomedical Imaging and Bioengineering (NIBIB). This opportunity supports mission-aligned projects in artificial intelligence, machine learning, and deep learning.
It includes technologies for processing and evaluating complex biomedical information, developing solutions to real-world healthcare problems, and building toward practical, patient-centered applications. Specific interest areas include medical image analysis, personalized medicine, EHR/EMR, clinical decision support, and computer-aided diagnostics.
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Artificial Intelligence, Machine Learning, and Deep Learning | National Institute of Biomedical Imaging and Bioengineering Artificial Intelligence, Machine Learning, and Deep Learning Director, National Centers for Biomedical Imaging and Bioengineering Division of Health Informatics Technologies (Informatics) Program Area: Artificial Intelligence, Machine Learning, and Deep Learning Division of Health Informatics Technologies (Informatics) Program Area: Artificial Intelligence, Machine Learning, and Deep Learning Supports the design and development of artificial intelligence, machine learning, and deep learning to enhance analysis of complex medical images and data.
The emphasis is on development of transformative machine intelligence-based systems, emerging tools, and modern technologies for diagnosing and recommending treatments for a range of diseases and health conditions. Unsupervised and semi-supervised techniques and methodologies are of particular interest.
Program priorities and areas of interest: clinical decision support systems analyzing complex patterns and images natural-language processing and understanding robotic and image guided surgery personalized imaging and treatment machine/deep learning-based segmentation, registration, etc. This program also supports: early-stage development of software, tools, and reusable convolutional neural networks data reduction, denoising, improving performance (health-promoting apps), and deep-learning based direct image reconstruction approaches that facilitate interoperability among annotations used in image training databases NIH Demystifies Vital Biomedical Tech for Congressional Staff Biomedical engineers and imaging researchers gave 45 congressional staff a glimpse of transformative medical technologies on the horizon, underscoring the crucial role of medical tools in human health.
AI tool can track effectiveness of multiple sclerosis treatments A new artificial intelligence (AI) tool that can help interpret and assess how well treatments are working for patients with multiple sclerosis (MS) has been developed by University College London researchers.
Source: University College London News Researchers lend expertise to improve treatment for childhood brain cancers Brain cancer is the second most common cancer in children after leukemia, and it is also the deadliest, due to the fact that brain tumors are diverse, resistant to treatments and often hard to access surgically.
A collaborative team of researchers at several institutions have developed a new way to profile brain cancers in children, paving the way for improved diagnostics and treatments. Source: UTSA Today NIH announces finalists of endometriosis diagnostics competition The National Institutes of Health (NIH) has selected four finalists with innovative, non-invasive technologies that seek to improve diagnosis of endometriosis.
Portable MRI, enhanced by AI, proves viable in brain imaging for dementia The low image quality of small, affordable MRI machines have prevented their widespread use. But a boost from AI could close the gap, bringing MRI to more patients.
According to the current listing, eligibility includes: Open to a wide range of research institutions, including universities, colleges, hospitals, and other non-profit and for-profit organizations. Confirm the full requirements in the official notice before applying.
The current listing shows varies (e.g., Trailblazer grants are up to $400,000 per year for three years for new and early-stage investigators). Verify award ceilings, matching requirements, and allowable costs in the official notice.
Artificial Intelligence, Machine Learning, and Deep Learning - National Institute of Biomedical Imaging and Bioengineering (NIBIB) is funded by National Institutes of Health (NIH) National Institute of Biomedical Imaging and Bioengineering (NIBIB). Verify program details on the funder's official page before applying.
Yes — this listing is flagged as national in scope, so applicants across the U.S. may apply, subject to the sponsor's other eligibility criteria.
Start from the official opportunity page linked in this listing — it carries the sponsor's submission instructions.
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