AIMC Topic: Deep Learning

Clear Filters Showing 9911 to 9920 of 28423 articles

Deep learning to automatically classify very large sets of preoperative and postoperative shoulder arthroplasty radiographs.

Journal of shoulder and elbow surgery
BACKGROUND: Joint arthroplasty registries usually lack information on medical imaging owing to the laborious process of observing and recording, as well as the lack of standard methods to transfer the imaging information to the registries, which can ...

Diagnosis with confidence: deep learning for reliable classification of laryngeal dysplasia.

Histopathology
BACKGROUND: Diagnosis of head and neck (HN) squamous dysplasias and carcinomas is critical for patient care, cure, and follow-up. It can be challenging, especially for grading intraepithelial lesions. Despite recent simplification in the last WHO gra...

Deep learning assisted measurement of echocardiographic left heart parameters: improvement in interobserver variability and workflow efficiency.

The international journal of cardiovascular imaging
Machine learning techniques designed to recognize views and perform measurements are increasingly used to address the need for automation of the interpretation of echocardiographic images. The current study was designed to determine whether a recentl...

Deep learning with citizen science data enables estimation of species diversity and composition at continental extents.

Ecology
Effective solutions to conserve biodiversity require accurate community- and species-level information at relevant, actionable scales and across entire species' distributions. However, data and methodological constraints have limited our ability to p...

Molecular geometric deep learning.

Cell reports methods
Molecular representation learning plays an important role in molecular property prediction. Existing molecular property prediction models rely on the de facto standard of covalent-bond-based molecular graphs for representing molecular topology at the...

Depressive Disorder Recognition Based on Frontal EEG Signals and Deep Learning.

Sensors (Basel, Switzerland)
Depressive disorder (DD) has become one of the most common mental diseases, seriously endangering both the affected person's psychological and physical health. Nowadays, a DD diagnosis mainly relies on the experience of clinical psychiatrists and sub...

Real-time dual prediction of intradialytic hypotension and hypertension using an explainable deep learning model.

Scientific reports
Both intradialytic hypotension (IDH) and hypertension (IDHTN) are associated with poor outcomes in hemodialysis patients, but a model predicting dual outcomes in real-time has never been developed. Herein, we developed an explainable deep learning mo...

Deep fit_predic: a novel integrated pyramid dilation EfficientNet-B3 scheme for fitness prediction system.

Computer methods in biomechanics and biomedical engineering
This study introduces novel deep learning (DL) techniques for effective fitness prediction using a person's health data. Initially, pre-processing is performed in which data cleaning, one-hot encoding and data normalization are performed. The pre-pro...

Discovery of type 2 diabetes mellitus with correlation and optimization driven hybrid deep learning approach.

Computer methods in biomechanics and biomedical engineering
Diabetes mellitus is a severe condition that has the potential to impair strength. The disease known as diabetes mellitus, which is a chronic condition, is brought on by a significant rise in blood glucose levels. The diagnosis of this condition is m...

Deep Learning-Based Survival Analysis for Receiving a Steatotic Donor Liver Versus Waiting for a Standard Liver.

Transplantation proceedings
BACKGROUND: An emerging strategy to expand the donor pool is the use of a steatotic donor liver (SDLs; ≥ 30% macrosteatosis on biopsy). With the obesity epidemic and prevalence of nonalcoholic fatty liver disease, SDLs have been reported in 59% of al...