AIMC Topic: Deep Learning

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Automated lesion detection in endoscopic imagery for small animal models - a pilot study.

Biomedizinische Technik. Biomedical engineering
OBJECTIVES: Small animal models, particularly mice, are crucial for studying gastrointestinal diseases like colorectal cancer. Tumor assessment via colonoscopy generates large video datasets, necessitating automated analysis due to limited resources ...

Molecular networking and deep learning synergy for bioactive metabolite discovery in L. plantarum-Fermented Sea buckthorn milk.

Food chemistry
This study investigated the metabolomic transformation of sea buckthorn milk fermented by Lactiplantibacillus plantarum to identify novel bioactive compounds and improve both nutritional and sensory attributes. An untargeted metabolomics workflow int...

Nondestructive detection of biogenic amines in muscle of Chinese mitten crab (Eriocheir sinensis): A basis for quality assessment using infrared spectroscopy and deep learning.

Food chemistry
Biogenic amines (BAs) are critical indicators of spoilage in aquatic products, but conventional detection methods are destructive and inefficient. This study proposes a nondestructive approach combining near-infrared (NIR) spectroscopy with deep lear...

Automatic specific absorption rate (SAR) prediction for hyperthermia treatment planning using deep learning method.

International journal of hyperthermia : the official journal of European Society for Hyperthermic Oncology, North American Hyperthermia Group
OBJECTIVE: To develop a deep learning method for fast and accurate prediction of Specific Absorption Rate (SAR) distributions in the human head to support real-time hyperthermia treatment planning (HTP) of brain cancer patients.

Early Detection of Lung Metastases in Breast Cancer Using YOLOv10 and Transfer Learning: A Diagnostic Accuracy Study.

Medical science monitor : international medical journal of experimental and clinical research
BACKGROUND This study used CT imaging analyzed with deep learning techniques to assess the diagnostic accuracy of lung metastasis detection in patients with breast cancer. The aim of the research was to create and verify a system for detecting malign...

Enhancing fake news detection with transformer-based deep learning: A multidisciplinary approach.

PloS one
The widespread dissemination of fake news presents a critical challenge to the integrity of digital information and erodes public trust. This urgent problem necessitates the development of sophisticated and reliable automated detection mechanisms. Th...

Smart load balancing in cloud computing: Integrating feature selection with advanced deep learning models.

PloS one
The increasing dependence on cloud computing as a cornerstone of modern technological infrastructures has introduced significant challenges in resource management. Traditional load-balancing techniques often prove inadequate in addressing cloud envir...

YOLOv5-aided paper-based microfluidic intelligent sensing platform for multiplex sweat biomarker analysis.

Biosensors & bioelectronics
Sweat, a biofluid rich in various biomarkers, offers significant potential for non-invasive health monitoring and disease screening. Colorimetric detection is well-suited for multi-analyte quantification and point-of-care testing in sweat analysis, w...

HPDAF: A practical tool for predicting drug-target binding affinity using multimodal features.

European journal of medicinal chemistry
Accurate prediction of drug-target binding affinity is crucial for efficient drug discovery and design, enabling researchers to better understand molecular interactions and accelerate the identification of promising drug candidates. Despite recent ad...

De-MSI: A Deep Learning-Based Data Denoising Method to Enhance Mass Spectrometry Imaging by Leveraging the Chemical Prior Knowledge.

Analytical chemistry
Mass spectrometry imaging (MSI) is a label-free technique that enables the visualization of the spatial distribution of thousands of ions within biosamples. Data denoising is the computational strategy aimed at enhancing the MSI data quality, providi...