With biomedical research transitioning into data-rich science, machine learning provides a powerful toolkit for extracting knowledge from large-scale biological data sets. The increasing availability of comprehensive kidney omics compendia (transcrip...
OBJECTIVE: To develop a radial basis function (RBF) neural network and investigate its performance in the estimation of glomerular filtration rate (GFR) for patients with chronic kidney disease.
Optical tissue transparency permits scalable cellular and molecular investigation of complex tissues in 3D. Adult human organs are particularly challenging to render transparent because of the accumulation of dense and sturdy molecules in decades-age...
Organ chips can recapitulate organ-level (patho)physiology, yet pharmacokinetic and pharmacodynamic analyses require multi-organ systems linked by vascular perfusion. Here, we describe an 'interrogator' that employs liquid-handling robotics, custom s...
Imaging biomarkers are being rapidly developed for early diagnosis and staging of disease. The development of these biomarkers requires advances in both image acquisition and analysis. Detecting and segmenting objects from images are often the first ...
Segmentation is fundamental to medical image analysis. Recent advances in fully convolutional networks has enabled automatic segmentation; however, high labeling efforts and difficulty in acquiring sufficient and high-quality training data is still a...
PURPOSE: Dual-energy computed tomography (DECT) has shown great potential in many clinical applications. By incorporating the information from two different energy spectra, DECT provides higher contrast and reveals more material differences of tissue...
The scale of biological microscopy has increased dramatically over the past ten years, with the development of new modalities supporting collection of high-resolution fluorescence image volumes spanning hundreds of microns if not millimeters. The siz...
Labeled medical imaging data is scarce and expensive to generate. To achieve generalizable deep learning models large amounts of data are needed. Standard data augmentation is a method to increase generalizability and is routinely performed. Generati...
Journal of evaluation in clinical practice
Nov 12, 2019
OBJECTIVES: In the context of the gradual development of artificial intelligence in health care, the clinical decision support systems (CDSS) play an increasing crucial role in improving the quality of the therapeutic and diagnostic efficiency in hea...
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