Scientists have developed a bioelectronic system driven by a machine learning algorithm that can shift the membrane voltage in living cells and maintain it at a set point for 10 hours.
Researchers have created a machine learning algorithm that can detect subtle signs of osteoarthritis on an MRI scan taken years before symptoms even begin.
A dose of artificial intelligence can speed the development of 3D-printed bioscaffolds that help injuries heal.
Digital phenotyping and machine learning have emerged as promising tools for monitoring patients with psychosis spectrum illnesses.
Researchers make the case that Artificial Intelligence tools have the potential to help researchers separate the wheat from the chaff.
Scientists have used machin -learning to organize the chemical diversity found in the ever-growing databases for the popular metal-organic framework materials.
The development of new medical technologies based on cutting-edge discoveries has accelerated during the coronavirus pandemic.
Researchers have shown that machine learning techniques helped an individual with paralysis learn to control a computer cursor using their brain activity.
Scientists and collaborators are using machine learning to address two key barriers to industrialization of two-photon lithography.
This is the first known time that AI has used causation instead of correlations to support doctors with diagnosis in simulated cases.
Researchers develop new machine learning approach that shows promise in predicting Necrotizing enterocolitis; could lead to improved medical decision-making in neonatal ICUs.
Researchers have developed an algorithm that not only predicts hospital readmissions of heart failure patients, but also tells you why these occur.
Researchers have shown that federated learning is successful in the context of brain imaging, by being able to analyze MRI scans of brain tumor patients and distinguish healthy brain tissue from cancerous regions.
Scientists have assembled a combination of data mining, machine-learning algorithms and compression-based analytics to bring the most useful data to the fore on an office computer.
Researchers have developed a machine learning model that can predict chemotherapy-associated nephrotoxicity.