Using deep imaging for higher resolution
Akasha Imaging, an MIT Media Lab spinout, provides efficient and cost-effective imaging with higher-resolution feature detection, tracking, and pose orientation.
Akasha Imaging, an MIT Media Lab spinout, provides efficient and cost-effective imaging with higher-resolution feature detection, tracking, and pose orientation.
Online course from the MIT Center for Advanced Virtuality seeks to empower students and educators to critically engage with media.
A new deep-learning algorithm trained to optimize doses of propofol to maintain unconsciousness during general anesthesia could augment patient monitoring.
Heather Kulik embraces computer models as “the only way to make a dent” in the vast number of potential materials that could solve important problems.
The technique can help predict a cell’s path over time, such as what type of cell it will become.
Assistant Professor Marzyeh Ghassemi explores how hidden biases in medical data could compromise artificial intelligence approaches.
New fellows are working on electronic health record algorithms, remote sensing data related to environmental health, and neural networks for the development of antibiotics.
The machine-learning model could help scientists speed the development of new medicines.
Doctoral candidate Nina Andrejević combines spectroscopy and machine learning techniques to identify novel and valuable properties in matter.
MIT neuroscientists have developed a computer model that can answer that question as well as the human brain.
A new method automatically describes, in natural language, what the individual components of a neural network do.
MIT scientist Rosalind Picard collaborates with clinicians to develop tools for mental health care delivery.
Senior research scientist and her team are designing intelligent systems that could someday transform the way we travel and consume energy.
MIT ocean and mechanical engineers are using advances in scientific computing to address the ocean’s many challenges, and seize its opportunities.
Scientists demonstrate that AI-risk models, paired with AI-designed screening policies, can offer significant and equitable improvements to cancer screening.