3 questions: Leveraging insights to enable clinical outcomes
Thomas Heldt, associate director of IMES, describes how he collaborates closely with MIT colleagues and others at Boston-area hospitals.
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Thomas Heldt, associate director of IMES, describes how he collaborates closely with MIT colleagues and others at Boston-area hospitals.
Novel method to scale phenotypic drug screening drastically reduces the number of input samples, costs, and labor required to execute a screen.
A research scientist and internationally recognized authority in the field of blood cell development reflects on 45 years at MIT.
Advisors commended for providing exceptional individualized mentoring for postdocs.
The innovations map the ocean floor and the brain, prevent heat stroke and cognitive injury, expand AI processing and quantum system capabilities, and introduce new fabrication approaches.
New statistical models based on physiological data from more than 100 surgeries provide objective, accurate measures of the body’s subconscious perception of pain.
MIT researchers find that the first dose primes the immune system, helping it to generate a strong response to the second dose, a week later.
MIT scientists’ discovery yields a potent immune response, could be used to develop a potential tumor vaccine.
In animal models, even low stimulation currents can sometimes still cause electrographic seizures, researchers found.
MD/PhD student Sayo Eweje seeks to develop new technologies for delivering RNA and protein therapies directly to the body’s cells.
Professor Ellen Roche is creating the next generation of medical devices to help repair hearts, lungs, and other tissues.
Professor who uses a cross-disciplinary approach to understand human diseases on a molecular and cellular level succeeds Elazer Edelman.
A mathematical method, validated with experimental data, provides a fast, reliable, and minimally invasive way of determining how to treat critical blood pressure changes during surgery or intensive care.
More accurate uncertainty estimates could help users decide about how and when to use machine-learning models in the real world.
Staff members receive recognition for their exceptional support of the MIT community.