Machine learning (ML) & artificial intelligence (AI) frameworks are expected to play a significant role in driving innovation and discovery in healthcare research. Examples of ML & AI applications in health care include medical imaging and diagnostics, robot-assisted surgeries, and remote care assistance. To foster research collaborations using ML & AI,...
Epilepsy affects nearly 3.5 million people in the United States and is linked to a five-fold increase in mortality. While epilepsy is often controlled with medication, 20-40% of patients are medically refractory and continue to experience seizures in spite of drug therapies. The alternative for...
Glaucoma is the second leading cause of blindness globally, with approximately 79.6 million people expected to be affected by the disease by 2020. Automated visual field (VF) testing remains the gold standard for identifying patients with glaucoma and judging worsening of disease. Approximately 5% of patients with glaucoma undergo rapid worsening of their VF test.
RAIL is an open structured artificial intelligence focused research collaboration based in the Hopkins Department of Radiology and Radiological Sciences. The group is comprised of physicians and scientists from Johns Hopkins Hospital, the Whiting School of Engineering, and the Applied Physics Laboratory,...
While artificial intelligence continues to transform healthcare, the tech has an Achilles heel: training AI systems to perform specific tasks...... Read More
Malone researchers presented a paper titled “Deep Labeling of fMRI Brain Networks Using Cloud Based Processing” at the 17th International Symposium...... Read More
The research team has received funding from the Retina Society to automate the early detection of sickle cell retinopathy....... Read More