AIMC Topic: Deep Learning

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Application of deep learning image assessment software VeriSee™ for diabetic retinopathy screening.

Journal of the Formosan Medical Association = Taiwan yi zhi
PURPOSE: To develop a deep learning image assessment software VeriSee™ and to validate its accuracy in grading the severity of diabetic retinopathy (DR).

Revealing cytotoxic substructures in molecules using deep learning.

Journal of computer-aided molecular design
In drug development, late stage toxicity issues of a compound are the main cause of failure in clinical trials. In silico methods are therefore of high importance to guide the early design process to reduce time, costs and animal testing. Technical a...

Deep Learning of Spatiotemporal Filtering for Fast Super-Resolution Ultrasound Imaging.

IEEE transactions on ultrasonics, ferroelectrics, and frequency control
Super-resolution ultrasound (SR-US) imaging is a new technique that breaks the diffraction limit and allows visualization of microvascular structures down to tens of micrometers. The image processing methods for the spatiotemporal filtering needed in...

Deep learning radiomic nomogram can predict the number of lymph node metastasis in locally advanced gastric cancer: an international multicenter study.

Annals of oncology : official journal of the European Society for Medical Oncology
BACKGROUND: Preoperative evaluation of the number of lymph node metastasis (LNM) is the basis of individual treatment of locally advanced gastric cancer (LAGC). However, the routinely used preoperative determination method is not accurate enough.

Training instance segmentation neural network with synthetic datasets for crop seed phenotyping.

Communications biology
In order to train the neural network for plant phenotyping, a sufficient amount of training data must be prepared, which requires time-consuming manual data annotation process that often becomes the limiting step. Here, we show that an instance segme...

DLI-IT: a deep learning approach to drug label identification through image and text embedding.

BMC medical informatics and decision making
BACKGROUND: Drug label, or packaging insert play a significant role in all the operations from production through drug distribution channels to the end consumer. Image of the label also called Display Panel or label could be used to identify illegal,...

A drug identification model developed using deep learning technologies: experience of a medical center in Taiwan.

BMC health services research
BACKGROUND: Issuing of correct prescriptions is a foundation of patient safety. Medication errors represent one of the most important problems in health care, with 'look-alike and sound-alike' (LASA) being the lead error. Existing solutions to preven...

DeshadowGAN: A Deep Learning Approach to Remove Shadows from Optical Coherence Tomography Images.

Translational vision science & technology
PURPOSE: To remove blood vessel shadows from optical coherence tomography (OCT) images of the optic nerve head (ONH).

Deep learning assessment of breast terminal duct lobular unit involution: Towards automated prediction of breast cancer risk.

PloS one
Terminal duct lobular unit (TDLU) involution is the regression of milk-producing structures in the breast. Women with less TDLU involution are more likely to develop breast cancer. A major bottleneck in studying TDLU involution in large cohort studie...