A Workshop for Brainstorming and Collaboration Focusing on Innovative Uses of Machine Learning in Tomographic Reconstruction.
Call for Paper: Special Issue on IEEE Transactions on Medical Imaging, “Federated Learning for Medical Imaging”
CAMCA paper “Federated learning for predicting clinical outcomes in patients with COVID-19” has now been published in Nature Medicine!
Last year, during the COVID19 pandemic, CAMCA researchers developed a deep learning model named CO-RISK which takes both chest X-ray images and EHR data to predict the level of supplemental oxygen a patient with COVID-19 symptoms may need 24 and 72 hours after arriving at the emergency department.
Call for Paper: Special Issue on Frontiers in Neuroscience, “Multi-Dimensional Characterization of Neuropsychiatric Disorders”
The human nervous system itself and its extensive connection with the human body are complex. There are various representations of nervous system with diverse observation methods and multiple dimensions of metrics. Similarly, in the field of medicine, almost all clinical diagnostic protocols for neuropsychiatric diseases/disorders involve multiple dimensions of individual characteristics. With the recent development of technology, scientists have been able to develop a more comprehensive understanding of neuropsychiatric disorders from multiple scales and dimensions.