AIMC Topic: Deep Learning

Clear Filters Showing 14931 to 14940 of 28423 articles

Training, validation, and clinical implementation of a deep-learning segmentation model for radiotherapy of loco-regional breast cancer.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
AIM: To train and validate a comprehensive deep-learning (DL) segmentation model for loco-regional breast cancer with the aim of clinical implementation.

A prediction model for pathological findings after neoadjuvant chemoradiotherapy for resectable locally advanced esophageal squamous cell carcinoma based on endoscopic images using deep learning.

The British journal of radiology
OBJECTIVES: To propose deep-learning (DL)-based predictive model for pathological complete response rate for resectable locally advanced esophageal squamous cell carcinoma (SCC) after neoadjuvant chemoradiotherapy (NCRT) with endoscopic images.

A Deep Learning Model for Accurate Diagnosis of Infection Using Antibody Repertoires.

Journal of immunology (Baltimore, Md. : 1950)
The adaptive immune receptor repertoire consists of the entire set of an individual's BCRs and TCRs and is believed to contain a record of prior immune responses and the potential for future immunity. Analyses of TCR repertoires via deep learning (DL...

A Deep Learning Approach for Quantifying Vocal Fold Dynamics During Connected Speech Using Laryngeal High-Speed Videoendoscopy.

Journal of speech, language, and hearing research : JSLHR
PURPOSE: Voice disorders are best assessed by examining vocal fold dynamics in connected speech. This can be achieved using flexible laryngeal high-speed videoendoscopy (HSV), which enables us to study vocal fold mechanics with high temporal details....

Deep-Learning-Based Algorithm for the Removal of Electromagnetic Interference Noise in Photoacoustic Endoscopic Image Processing.

Sensors (Basel, Switzerland)
Despite all the expectations for photoacoustic endoscopy (PAE), there are still several technical issues that must be resolved before the technique can be successfully translated into clinics. Among these, electromagnetic interference (EMI) noise, in...

A Driver Gaze Estimation Method Based on Deep Learning.

Sensors (Basel, Switzerland)
Car crashes are among the top ten leading causes of death; they could mainly be attributed to distracted drivers. An advanced driver-assistance technique (ADAT) is a procedure that can notify the driver about a dangerous scenario, reduce traffic cras...

A Deep Learning Method Approach for Sleep Stage Classification with EEG Spectrogram.

International journal of environmental research and public health
The classification of sleep stages is an important process. However, this process is time-consuming, subjective, and error-prone. Many automated classification methods use electroencephalogram (EEG) signals for classification. These methods do not cl...

Deep Learning for Infant Cry Recognition.

International journal of environmental research and public health
Recognizing why an infant cries is challenging as babies cannot communicate verbally with others to express their wishes or needs. This leads to difficulties for parents in identifying the needs and the health of their infants. This study used deep l...

Cell cycle gene regulation dynamics revealed by RNA velocity and deep-learning.

Nature communications
Despite the fact that the cell cycle is a fundamental process of life, a detailed quantitative understanding of gene regulation dynamics throughout the cell cycle is far from complete. Single-cell RNA-sequencing (scRNA-seq) technology gives access to...

Diagnostic accuracy of code-free deep learning for detection and evaluation of posterior capsule opacification.

BMJ open ophthalmology
OBJECTIVE: To train and validate a code-free deep learning system (CFDLS) on classifying high-resolution digital retroillumination images of posterior capsule opacification (PCO) and to discriminate between clinically significant and non-significant ...