AIMC Topic: Deep Learning

Clear Filters Showing 3711 to 3720 of 28423 articles

Deep learning based prediction of depression and anxiety in patients with type 2 diabetes mellitus using regional electronic health records.

International journal of medical informatics
BACKGROUND: Depression and anxiety are prevalent mental health conditions among individuals with type 2 diabetes mellitus (T2DM), who exhibit unique vulnerabilities and etiologies. However, existing approaches fail to fully utilize regional heterogen...

Hip prosthesis failure prediction through radiological deep sequence learning.

International journal of medical informatics
BACKGROUND: Existing deep learning studies for the automated detection of hip prosthesis failure only consider the last available radiographic image. However, using longitudinal data is thought to improve the prediction, by combining temporal and spa...

SAF-IS: A spatial annotation free framework for instance segmentation of surgical tools.

Medical image analysis
Instance segmentation of surgical instruments is a long-standing research problem, crucial for the development of many applications for computer-assisted surgery. This problem is commonly tackled via fully-supervised training of deep learning models,...

Gait Video-Based Prediction of Severity of Cerebellar Ataxia Using Deep Neural Networks.

Movement disorders : official journal of the Movement Disorder Society
BACKGROUND: Pose estimation algorithms applied to two-dimensional videos evaluate gait disturbances; however, a few studies have used this method to evaluate ataxic gait.

A multimodal deep learning model for cervical pre-cancers and cancers prediction: Development and internal validation study.

Computers in biology and medicine
BACKGROUND: The current cervical cancer screening and diagnosis have limitations due to their subjectivity and lack of reproducibility. We describe the development of a deep learning (DL)-based diagnostic risk prediction model and evaluate its potent...

Interpretable COVID-19 chest X-ray detection based on handcrafted feature analysis and sequential neural network.

Computers in biology and medicine
Deep learning methods have significantly improved medical image analysis, particularly in detecting COVID-19 chest X-rays. Nonetheless, these methodologies frequently inhibit some drawbacks, such as limited interpretability, extensive computational r...

Deep learning-based image classification reveals heterogeneous execution of cell death fates during viral infection.

Molecular biology of the cell
Cell fate decisions, such as proliferation, differentiation, and death, are driven by complex molecular interactions and signaling cascades. While significant progress has been made in understanding the molecular determinants of these processes, hist...

Utilizing deep learning for automatic segmentation of the cochleae in temporal bone computed tomography.

Acta radiologica (Stockholm, Sweden : 1987)
BackgroundSegmentation of the cochlea in temporal bone computed tomography (CT) is the basis for image-guided otologic surgery. Manual segmentation is time-consuming and laborious.PurposeTo assess the utility of deep learning analysis in automatic se...

Discrimination of unsound soybeans using hyperspectral imaging: A deep learning method based on dual-channel feature fusion strategy and attention mechanism.

Food research international (Ottawa, Ont.)
The application of high-level data fusion in the detection of agricultural products still presents a significant challenge. In this study, dual-channel feature fusion model (DCFFM) with attention mechanism was proposed to optimize the utilization of ...