AIMC Topic: Deep Learning

Clear Filters Showing 10161 to 10170 of 28423 articles

The impact of deep learning reconstruction in low dose computed tomography on the evaluation of interstitial lung disease.

PloS one
To evaluate the effect of the deep learning model reconstruction (DLM) method in terms of image quality and diagnostic agreement in low-dose computed tomography (LDCT) for interstitial lung disease (ILD), 193 patients who underwent LDCT for suspected...

TumorDetNet: A unified deep learning model for brain tumor detection and classification.

PloS one
Accurate diagnosis of the brain tumor type at an earlier stage is crucial for the treatment process and helps to save the lives of a large number of people worldwide. Because they are non-invasive and spare patients from having an unpleasant biopsy, ...

THA-AID: Deep Learning Tool for Total Hip Arthroplasty Automatic Implant Detection With Uncertainty and Outlier Quantification.

The Journal of arthroplasty
BACKGROUND: Revision total hip arthroplasty (THA) requires preoperatively identifying in situ implants, a time-consuming and sometimes unachievable task. Although deep learning (DL) tools have been attempted to automate this process, existing approac...

Developing a deep learning model for sleep stage prediction in obstructive sleep apnea cohort using 60 GHz frequency-modulated continuous-wave radar.

Journal of sleep research
Given the significant impact of sleep on overall health, radar technology offers a promising, non-invasive, and cost-effective avenue for the early detection of sleep disorders, even prior to relying on polysomnography (PSG)-based classification. In ...

DeepHistoNet: A robust deep-learning model for the classification of hepatocellular, lung, and colon carcinoma.

Microscopy research and technique
In recent days, non-communicable diseases (NCDs) require more attention since they require specialized infrastructure for treatment. As per the cancer population registry estimate, nearly 800,000 new cancer cases will be detected yearly. The statisti...

Open-Source 3D Morphing Software for Facial Plastic Surgery and Facial Landmark Detection Research and Open Access Face Data Set Based on Deep Learning (Artificial Intelligence) Generated Synthetic 3D Models.

Facial plastic surgery & aesthetic medicine
The scarcity of 3D facial models presents a significant hurdle for researchers and educators. Gathering such data demands substantial resources. To introduce an open-source 3D morphing software to generate 3D facial data sets for research and to pr...

EQUIBIND: A geometric deep learning-based protein-ligand binding prediction method.

Drug discoveries & therapeutics
Structure-based virtual screening plays a critical role in drug discovery. However, numerous docking programs, such as AutoDock Vina and Glide, are time-consuming due to the necessity of generating numerous molecular conformations and executing steps...

Detection and subtyping of hepatic echinococcosis from plain CT images with deep learning: a retrospective, multicentre study.

The Lancet. Digital health
BACKGROUND: Hepatic echinococcosis is a severe endemic disease in some underdeveloped rural areas worldwide. Qualified physicians are in short supply in such areas, resulting in low rates of accurate diagnosis of this condition. In this study, we aim...

External validation of deep learning-based automated detection algorithm for chest radiograph: practical issues in outpatient clinic.

Acta radiologica (Stockholm, Sweden : 1987)
BACKGROUND: There have been no reports on diagnostic performance of deep learning-based automated detection (DLAD) for thoracic diseases in real-world outpatient clinic.

Validation of a Deep Learning Algorithm for Continuous, Real-Time Detection of Atrial Fibrillation Using a Wrist-Worn Device in an Ambulatory Environment.

Journal of the American Heart Association
BACKGROUND: Wearable devices may be useful for identification, quantification and characterization, and management of atrial fibrillation (AF). To date, consumer wrist-worn devices for AF detection using photoplethysmography-based algorithms perform ...