AIMC Topic: Deep Learning

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Reasoning-Driven Food Energy Estimation via Multimodal Large Language Models.

Nutrients Mar 24, 2025
Image-based food energy estimation is essential for user-friendly food tracking applications, enabling individuals to monitor their dietary intake through smartphones or AR devices. However, existing deep learning approaches struggle to recognize a ...
Humans Language Nutrition Assessment Energy Intake Deep Learning Large Language Models
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Establishment of a deep-learning-assisted recurrent nasopharyngeal carcinoma detecting simultaneous tactic (DARNDEST) with high cost-effectiveness based on magnetic resonance images: a multicenter study in an endemic area.

Cancer imaging : the official publication of the International Cancer Imaging Society Mar 24, 2025
BACKGROUND: To investigate the feasibility of detecting local recurrent nasopharyngeal carcinoma (rNPC) using unenhanced magnetic resonance images (MRI) and optimize a layered management strategy for follow-up with a deep learning model.
Nasopharyngeal Neoplasms Endemic Diseases Middle Aged Deep Learning Magnetic Resonance Imaging Cost-Benefit Analysis Adult Feasibility Studies Nasopharyngeal Carcinoma Sensitivity and Specificity Humans Neoplasm Recurrence, Local Male Female Aged
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Constructing an artificial intelligence-assisted system for the assessment of gastroesophageal valve function based on the hill classification (with video).

BMC medical informatics and decision making Mar 24, 2025
OBJECTIVE: In the functional assessment of the esophagogastric junction (EGJ), the endoscopic Hill classification plays a pivotal role in classifying the morphology of the gastroesophageal flap valve (GEFV). This study aims to develop an artificial i...
Gastroscopy Esophagogastric Junction Artificial Intelligence Deep Learning Video Recording Humans
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Intelligent detection and grading diagnosis of fresh rib fractures based on deep learning.

BMC medical imaging Mar 24, 2025
BACKGROUND: Accurate detection and grading of fresh rib fractures are crucial for patient management but remain challenging due to the complexity of rib structures on CT images.
Adult Male Middle Aged Female Aged Aged, 80 and over Deep Learning Humans Rib Fractures Retrospective Studies Tomography, X-Ray Computed
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A deep learning model based on Mamba for automatic segmentation in cervical cancer brachytherapy.

Scientific reports Mar 24, 2025
This study developed and evaluated an automatic segmentation model based on the Mamba framework (AM-UNet) for rapid and precise delineation of high-risk clinical target volume (HRCTV) and organs at risk (OARs) in cervical cancer brachytherapy. Using ...
Female Aged Adult Uterine Cervical Neoplasms Humans Tomography, X-Ray Computed Radiotherapy Planning, Computer-Assisted Brachytherapy Radiotherapy Dosage Middle Aged Deep Learning Organs at Risk
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Two-tier nature inspired optimization-driven ensemble of deep learning models for effective autism spectrum disorder diagnosis in disabled persons.

Scientific reports Mar 24, 2025
Autism spectrum disorder (ASD) includes a varied set of neuropsychiatric illnesses. This disorder is described by a definite grade of loss in social communication, academic functioning, personal contact, and limited and repetitive behaviours. Individ...
Persons with Disabilities Humans Machine Learning Autism Spectrum Disorder Algorithms Male Deep Learning
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Early prediction of intraventricular hemorrhage in very low birth weight infants using deep neural networks with attention in low-resource settings.

Scientific reports Mar 24, 2025
Early prediction of intraventricular hemorrhage (IVH) in very low-birthweight infants (VLBWIs) remains challenging because of multifactorial risk factors. IVH often occurs within a few hours after birth, yet its onset cannot be reliably predicted usi...
Female Infant, Newborn Risk Factors Humans Neural Networks, Computer Birth Weight Gestational Age Cerebral Intraventricular Hemorrhage Infant, Very Low Birth Weight Male Deep Learning Cerebral Hemorrhage
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Weighted-VAE: A deep learning approach for multimodal data generation applied to experimental T. cruzi infection.

PloS one Mar 24, 2025
Chagas disease (CD), caused by the protozoan parasite Trypanosoma cruzi (T. cruzi), represents a major public health concern in most of the American continent and causes 12,000 deaths every year. CD clinically manifests in two phases (acute and chron...
Disease Models, Animal Deep Learning Trypanosoma cruzi Humans Chagas Disease Mice Animals Electrocardiography Echocardiography
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Optimising window size of semantic of classification model for identification of in-text citations based on context and intent.

PloS one Mar 24, 2025
Citations in scientific literature act as channels for the sharing, transfer, and development of scientific knowledge. However, not all citations hold the same significance. Numerous taxonomies and machine learning models have been developed to analy...
Humans Machine Learning Deep Learning Natural Language Processing Semantics
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Technical implications of a novel deep learning system in the segmentation and evaluation of computed tomography angiography before transcatheter aortic valve replacement.

Therapeutic advances in cardiovascular disease Mar 24, 2025
OBJECTIVE: The goal of this study was to compare the computed tomography angiography scans of the segmentation results from the Cvpilot, 3mensio, and Volume Viewer systems to explore the practicability of the Cvpilot system in the automatic segmentat...
Computed Tomography Angiography Transcatheter Aortic Valve Replacement Retrospective Studies Aortography Female Aged Deep Learning Reproducibility of Results Predictive Value of Tests Humans Aged, 80 and over Aortic Valve Stenosis Radiographic Image Interpretation, Computer-Assisted Male Aortic Valve Multidetector Computed Tomography
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