Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine
Aug 5, 2020
OBJECTIVES: Deep learning for medical imaging analysis uses convolutional neural networks pretrained on ImageNet (Stanford Vision Lab, Stanford, CA). Little is known about how such color- and scene-rich standard training images compare quantitatively...
Journal of chemical information and modeling
Jul 31, 2020
Recently, machine learning has been successfully applied to the prediction of nuclear magnetic resonance (NMR) chemical shifts. To build a prediction model, the existing methods require a training data set that comprises molecules whose NMR-active at...
Microsurgical tools offer a path to less invasive clinical procedures with improved access, reduced trauma, and better recovery outcomes. There are a variety of rigid and flexible endoscopic devices that have significantly advanced diagnostics and mi...
OBJECTIVES: We aimed to evaluate the ability of feed-forward neural networks (fNNs) to predict the neurodevelopmental outcome (NDO) of very preterm neonates (VPIs) at 12 months corrected age by using biomarkers of cerebral MR proton spectroscopy (H-M...
Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
Jul 4, 2020
PURPOSE: To estimate the prognostic value of deep learning (DL) magnetic resonance (MR)-based radiomics for stage T3N1M0 nasopharyngeal carcinoma (NPC) patients receiving induction chemotherapy (ICT) prior to concurrent chemoradiotherapy (CCRT).
Chemistry (Weinheim an der Bergstrasse, Germany)
Jun 25, 2020
Since the concept of deep learning (DL) was formally proposed in 2006, it has had a major impact on academic research and industry. Nowadays, DL provides an unprecedented way to analyze and process data with demonstrated great results in computer vis...
This study represents a rapid and non-destructive approach based on mid-infrared (MIR) spectroscopy, time domain nuclear magnetic resonance (TD-NMR), and machine learning classification models (ML) for monitoring soluble pectin content (SPC) changes ...
This study aimed to develop a diagnostic algorithm for preoperative differentiating uterine sarcoma from leiomyoma through a supervised machine-learning method using multi-parametric MRI. A total of 65 participants with 105 myometrial tumors were inc...
Remodeling of tissue microvasculature commonly promotes neoplastic growth; however, there is no imaging modality in oncology yet that noninvasively quantifies microvascular changes in clinical routine. Although blood capillaries cannot be resolved in...
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