Recent advances in multiplexed single-cell transcriptomics experiments facilitate the high-throughput study of drug and genetic perturbations. However, an exhaustive exploration of the combinatorial perturbation space is experimentally unfeasible. Therefore, computational methods are needed to predict, interpret, and prioritize perturbations.
View Article and Find Full Text PDFAccelerating MRI scans is one of the principal outstanding problems in the MRI research community. Towards this goal, we hosted the second fastMRI competition targeted towards reconstructing MR images with subsampled k-space data. We provided participants with data from 7,299 clinical brain scans (de-identified via a HIPAA-compliant procedure by NYU Langone Health), holding back the fully-sampled data from 894 of these scans for challenge evaluation purposes.
View Article and Find Full Text PDFThe rapid spread of COVID-19 cases in recent months has strained hospital resources, making rapid and accurate triage of patients presenting to emergency departments a necessity. Machine learning techniques using clinical data such as chest X-rays have been used to predict which patients are most at risk of deterioration. We consider the task of predicting two types of patient deterioration based on chest X-rays: adverse event deterioration (i.
View Article and Find Full Text PDFDeep learning (DL) image reconstruction has the potential to disrupt the current state of MRI by significantly decreasing the time required for MRI examinations. Our goal was to use DL to accelerate MRI to allow a 5-minute comprehensive examination of the knee without compromising image quality or diagnostic accuracy. A DL model for image reconstruction using a variational network was optimized.
View Article and Find Full Text PDFPurpose: To advance research in the field of machine learning for MR image reconstruction with an open challenge.
Methods: We provided participants with a dataset of raw k-space data from 1,594 consecutive clinical exams of the knee. The goal of the challenge was to reconstruct images from these data.
A publicly available dataset containing k-space data as well as Digital Imaging and Communications in Medicine image data of knee images for accelerated MR image reconstruction using machine learning is presented.
View Article and Find Full Text PDFThe present epidemic of diabetes is resulting in a worldwide increase in cardiovascular and microvascular complications including retinopathy. Current thinking has focused on local influences in the retina as being responsible for development of this diabetic complication. However, the contribution of circulating cells in maintenance, repair, and dysfunction of the vasculature is now becoming appreciated.
View Article and Find Full Text PDFActa Crystallogr Sect F Struct Biol Cryst Commun
July 2009
EpsH is a minor pseudopilin protein of the Vibrio cholerae type II secretion system. A truncated form of EpsH with a C-terminal noncleavable His tag was constructed and expressed in Escherichia coli, purified and crystallized by sitting-drop vapor diffusion. A complete data set was collected to 1.
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