AIMC Topic: Deep Learning

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Multi-modal dataset creation for federated learning with DICOM-structured reports.

International journal of computer assisted radiology and surgery Feb 3, 2025
Purpose Federated training is often challenging on heterogeneous datasets due to divergent data storage options, inconsistent naming schemes, varied annotation procedures, and disparities in label quality. This is particularly evident in the emerging...
Datasets as Topic Radiology Information Systems Federated Learning Tomography, X-Ray Computed Deep Learning Electrocardiography Humans
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Convolutional Neural Networks Assisted Peak Classification in Targeted LC-HRMS/MS for Equine Doping Control Screening Analyses.

Analytical chemistry Feb 3, 2025
Doping control screening analyses usually involve visual inspection of extracted ion chromatograms (EIC) by a trained analytical chemist, followed by further investigations if needed. This task is both highly repetitive and time-consuming, given the ...
Convolutional Neural Networks Chromatography, High Pressure Liquid Doping in Sports Neural Networks, Computer Discriminant Analysis Tandem Mass Spectrometry Animals Horses Deep Learning
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Development and Evaluation of a Deep Learning-Based Pulmonary Hypertension Screening Algorithm Using a Digital Stethoscope.

Journal of the American Heart Association Feb 3, 2025
BACKGROUND: Despite the poor outcomes related to the presence of pulmonary hypertension, it often goes undiagnosed in part because of low suspicion and screening tools not being easily accessible such as echocardiography. A new readily available scre...
Male Humans Stethoscopes Echocardiography Deep Learning Reproducibility of Results Algorithms Pulmonary Artery Middle Aged Predictive Value of Tests Female Aged Phonocardiography Hypertension, Pulmonary
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Comparative analysis of the DCNN and HFCNN Based Computerized detection of liver cancer.

BMC medical imaging Feb 3, 2025
Liver cancer detection is critically important in the discipline of biomedical image testing and diagnosis. Researchers have explored numerous machine learning (ML) techniques and deep learning (DL) approaches aimed at the automated recognition of li...
Radiographic Image Interpretation, Computer-Assisted Tomography, X-Ray Computed Humans Deep Learning Neural Networks, Computer Liver Neoplasms
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An explainable deep learning model for diabetic foot ulcer classification using swin transformer and efficient multi-scale attention-driven network.

Scientific reports Feb 3, 2025
Diabetic Foot Ulcer (DFU) is a severe complication of diabetes mellitus, resulting in significant health and socio-economic challenges for the diagnosed individual. Severe cases of DFU can lead to lower limb amputation in diabetic patients, making th...
Diabetic Foot Neural Networks, Computer Algorithms Humans Deep Learning
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Fundus camera-based precision monitoring of blood vitamin A level for Wagyu cattle using deep learning.

Scientific reports Feb 3, 2025
In the wagyu industry worldwide, high-quality marbling beef is produced by promoting intramuscular fat deposition during cattle fattening stage through dietary vitamin A control. Thus, however, cattle become susceptible to either vitamin A deficiency...
Animals Deep Learning Photography Vitamin A Cattle Vitamin A Deficiency Cattle Diseases Fundus Oculi
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Deep learning and radiomics for gastric cancer serosal invasion: automated segmentation and multi-machine learning from two centers.

Journal of cancer research and clinical oncology Feb 3, 2025
OBJECTIVE: The objective of this study is to develop an automated method for segmenting spleen computed tomography (CT) images using a deep learning model. This approach is intended to address the limitations of manual segmentation, which is known to...
Neoplasm Invasiveness Spleen Deep Learning Tomography, X-Ray Computed Image Processing, Computer-Assisted Female Nomograms Aged Male Adult Middle Aged Stomach Neoplasms Humans Radiomics Machine Learning
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Deep learning powered single-cell clustering framework with enhanced accuracy and stability.

Scientific reports Feb 3, 2025
Single-cell RNA sequencing (scRNA-seq) has revolutionized the field of cellular diversity research. Unsupervised clustering, a key technique in this exploration, allows for the identification of distinct cell types within a population. Graph-based de...
Sequence Analysis, RNA Cluster Analysis Single-Cell Analysis RNA-Seq Humans Algorithms Gene Expression Profiling Deep Learning
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AFMDD: Analyzing Functional Connectivity Feature of Major Depressive Disorder by Graph Neural Network-Based Model.

Journal of computational biology : a journal of computational molecular cell biology Feb 3, 2025
The extraction of biomarkers from functional connectivity (FC) in the brain is of great significance for the diagnosis of mental disorders. In recent years, with the development of deep learning, several methods have been proposed to assist in the di...
Humans Brain Depressive Disorder, Major Deep Learning Neural Networks, Computer Algorithms Biomarkers Graph Neural Networks
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Adaptive wavelet base selection for deep learning-based ECG diagnosis: A reinforcement learning approach.

PloS one Feb 3, 2025
Electrocardiogram (ECG) signals are crucial in diagnosing cardiovascular diseases (CVDs). While wavelet-based feature extraction has demonstrated effectiveness in deep learning (DL)-based ECG diagnosis, selecting the optimal wavelet base poses a sign...
Signal Processing, Computer-Assisted Cardiovascular Diseases Humans Deep Learning Wavelet Analysis Algorithms Electrocardiography
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