AIMC Topic: Deep Learning

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Deep Learning Solution for Quantification of Fluorescence Particles on a Membrane.

Sensors (Basel, Switzerland)
The detection and quantification of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) virus particles in ambient waters using a membrane-based in-gel loop-mediated isothermal amplification (mgLAMP) method can play an important role in larg...

Early Identification of Crop Type for Smallholder Farming Systems Using Deep Learning on Time-Series Sentinel-2 Imagery.

Sensors (Basel, Switzerland)
Climate change and the COVID-19 pandemic have disrupted the food supply chain across the globe and adversely affected food security. Early estimation of staple crops can assist relevant government agencies to take timely actions for ensuring food sec...

Identification of Key MicroRNAs and Genes between Colorectal Adenoma and Colorectal Cancer via Deep Learning on GEO Databases and Bioinformatics.

Contrast media & molecular imaging
BACKGROUND: Deep learning techniques are gaining momentum in medical research. Colorectal adenoma (CRA) is a precancerous lesion that may develop into colorectal cancer (CRC) and its etiology and pathogenesis are unclear. This study aims to identify ...

Deep learning-assisted smartphone-based portable and visual ratiometric fluorescence device integrated intelligent gel label for agro-food freshness detection.

Food chemistry
Here, a smartphone-assisted dual-color ratiometric fluorescence smart gel label-based visual sensing platform was constructed for real-time evaluation of the freshness of agro-food based on the biogenic amines responses. Green-emission fluorescence c...

A deep learning model with data integration of ultrasound contrast-enhanced micro-flow cines, B-mode images, and clinical parameters for diagnosing significant liver fibrosis in patients with chronic hepatitis B.

European radiology
OBJECTIVE: To develop and investigate a deep learning model with data integration of ultrasound contrast-enhanced micro-flow (CEMF) cines, B-mode images, and patients' clinical parameters to improve the diagnosis of significant liver fibrosis (≥ F2) ...

Leukocyte deep learning classification assessment using Shapley additive explanations algorithm.

International journal of laboratory hematology
INTRODUCTION: A peripheral blood smear is a basic test for hematological disease diagnosis. This test is performed manually in many places worldwide, which requires both time and qualified staff. Large laboratories are equipped with digital morpholog...

Identification of Active Pulmonary Tuberculosis Among Patients With Positive Interferon-Gamma Release Assay Results: Value of a Deep Learning-based Computer-aided Detection System in Different Scenarios of Implementation.

Journal of thoracic imaging
PURPOSE: To evaluate the accuracy of a deep learning-based computer-aided detection (CAD) system in identifying active pulmonary tuberculosis on chest radiographs (CRs) of patients with positive interferon-gamma release assay (IGRA) results in differ...

Real-Time Automated Segmentation of Median Nerve in Dynamic Ultrasonography Using Deep Learning.

Ultrasound in medicine & biology
OBJECTIVE: The morphological dynamics of the median nerve across the level extracted from dynamic ultrasonography are valuable for the diagnosis and evaluation of carpal tunnel syndrome (CTS), but the data extraction requires tremendous labor to manu...

DapNet-HLA: Adaptive dual-attention mechanism network based on deep learning to predict non-classical HLA binding sites.

Analytical biochemistry
Human leukocyte antigen (HLA) plays a vital role in immunomodulatory function. Studies have shown that immunotherapy based on non-classical HLA has essential applications in cancer, COVID-19, and allergic diseases. However, there are few deep learnin...

A deep learning based two-layer predictor to identify enhancers and their strength.

Methods (San Diego, Calif.)
The enhancer is a DNA sequence that can increase the activity of promoters and thus speed up the frequency of gene transcription. The enhancer plays an essential role in activating gene expression. Currently, gene sequencing technology has been devel...