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Deep learned tissue "fingerprints" classify breast cancers by ER/PR/Her2 status from H&E images.

Scientific reports
Because histologic types are subjective and difficult to reproduce between pathologists, tissue morphology often takes a back seat to molecular testing for the selection of breast cancer treatments. This work explores whether a deep-learning algorith...

Identification of the Facial Features of Patients With Cancer: A Deep Learning-Based Pilot Study.

Journal of medical Internet research
BACKGROUND: Cancer has become the second leading cause of death globally. Most cancer cases are due to genetic mutations, which affect metabolism and result in facial changes.

Predicting Glaucoma before Onset Using Deep Learning.

Ophthalmology. Glaucoma
PURPOSE: To assess the accuracy of deep learning models to predict glaucoma development from fundus photographs several years before disease onset.

Deep learning in rare disease. Detection of tubers in tuberous sclerosis complex.

PloS one
OBJECTIVE: To develop and test a deep learning algorithm to automatically detect cortical tubers in magnetic resonance imaging (MRI), to explore the utility of deep learning in rare disorders with limited data, and to generate an open-access deep lea...

Prediction of Postoperative Length of Hospital Stay Based on Differences in Nursing Narratives in Elderly Patients with Epithelial Ovarian Cancer.

Methods of information in medicine
OBJECTIVES:  The current study sought to evaluate whether nursing narratives can be used to predict postoperative length of hospital stay (LOS) following curative surgery for ovarian cancer.

Estimation of age in unidentified patients via chest radiography using convolutional neural network regression.

Emergency radiology
PURPOSE: Patient age has important clinical utility for refining a differential diagnosis in radiology. Here, we evaluate the potential for convolutional neural network models to predict patient age based on anterior-posterior chest radiographs for i...

Automated detection of COVID-19 cases using deep neural networks with X-ray images.

Computers in biology and medicine
The novel coronavirus 2019 (COVID-2019), which first appeared in Wuhan city of China in December 2019, spread rapidly around the world and became a pandemic. It has caused a devastating effect on both daily lives, public health, and the global econom...

Efficient Position Decoding Methods Based on Fluorescence Calcium Imaging in the Mouse Hippocampus.

Neural computation
Large-scale fluorescence calcium imaging methods have become widely adopted for studies of long-term hippocampal and cortical neuronal dynamics. Pyramidal neurons of the rodent hippocampus show spatial tuning in freely foraging or head-fixed navigati...

Machine learning approach for prediction of hearing preservation in vestibular schwannoma surgery.

Scientific reports
In vestibular schwannoma patients with functional hearing status, surgical resection while preserving the hearing is feasible. Hearing levels, tumor size, and location of the tumor have been known to be candidates of predictors. We used a machine lea...

Comparison of CBCT based synthetic CT methods suitable for proton dose calculations in adaptive proton therapy.

Physics in medicine and biology
In-room imaging is a prerequisite for adaptive proton therapy. The use of onboard cone-beam computed tomography (CBCT) imaging, which is routinely acquired for patient position verification, can enable daily dose reconstructions and plan adaptation d...