AIMC Topic: Deep Learning

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Deep Learning Segmentation of the Right Ventricle in Cardiac MRI: The M&Ms Challenge.

IEEE journal of biomedical and health informatics
In recent years, several deep learning models have been proposed to accurately quantify and diagnose cardiac pathologies. These automated tools heavily rely on the accurate segmentation of cardiac structures in MRI images. However, segmentation of th...

SLEEP-SEE-THROUGH: Explainable Deep Learning for Sleep Event Detection and Quantification From Wearable Somnography.

IEEE journal of biomedical and health informatics
Evidence is rapidly accumulating that multifactorial nocturnal monitoring, through the coupling of wearable devices and deep learning, may be disruptive for early diagnosis and assessment of sleep disorders. In this work, optical, differential air-pr...

Deep Learning Identifies Intelligible Predictors of Poor Prognosis in Chronic Kidney Disease.

IEEE journal of biomedical and health informatics
Early diagnosis and prediction of chronic kidney disease (CKD) progress within a given duration are critical to ensure personalized treatment, which could improve patients' quality of life and prolong survival time. In this study, we explore the inte...

Federated Learning of Generative Image Priors for MRI Reconstruction.

IEEE transactions on medical imaging
Multi-institutional efforts can facilitate training of deep MRI reconstruction models, albeit privacy risks arise during cross-site sharing of imaging data. Federated learning (FL) has recently been introduced to address privacy concerns by enabling ...

Deep learning enhanced ultra-fast SPECT/CT bone scan in patients with suspected malignancy: quantitative assessment and clinical performance.

Physics in medicine and biology
. To evaluate the clinical performance of deep learning-enhanced ultrafast single photon emission computed tomography/computed tomography (SPECT/CT) bone scans in patients with suspected malignancy.. In this prospective study, 102 patients with poten...

Cracking double-blind review: Authorship attribution with deep learning.

PloS one
Double-blind peer review is considered a pillar of academic research because it is perceived to ensure a fair, unbiased, and fact-centered scientific discussion. Yet, experienced researchers can often correctly guess from which research group an anon...

Artificial intelligence for evaluating the risk of gastric cancer: reliable detection and scoring of intestinal metaplasia with deep learning algorithms.

Gastrointestinal endoscopy
BACKGROUND AND AIMS: Gastric cancer (GC) is associated with chronic gastritis. To evaluate the risk, the Operative Link on Gastric Intestinal Metaplasia Assessment (OLGIM) system was constructed and showed a higher GC risk in stage III or IV patients...

Implementation of transfer learning for the segmentation of human mesenchymal stem cells-A validation study.

Tissue & cell
INTRODUCTION: Stem cell therapy has been gaining interest in the regeneration rather than repair of lost human tissues. However, the manual analysis of stem cells prior to implantation is a cumbersome task that can be automated to improve the efficie...

DL4SciVis: A State-of-the-Art Survey on Deep Learning for Scientific Visualization.

IEEE transactions on visualization and computer graphics
Since 2016, we have witnessed the tremendous growth of artificial intelligence+visualization (AI+VIS) research. However, existing survey articles on AI+VIS focus on visual analytics and information visualization, not scientific visualization (SciVis)...

A Deep Learning Regression Model for Photonic Crystal Fiber Sensor With XAI Feature Selection and Analysis.

IEEE transactions on nanobioscience
A Deep Learning Multi-output regression model is employed to correctly model the relationships between optical design parameters of an asymmetric Twin Elliptical Core Photonic Crystal Fiber (TEC-PCF) and its sensing performances. TEC-PCF acts as a bi...