AIMC Topic: Deep Learning
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Transfer learning and data augmentation for glucose concentration prediction from colorimetric biosensor images.
Mikrochimica acta
Apr 8, 2025
A deep learning algorithm is introduced to accurately predict glucose concentrations using colorimetric paper sensor (CPS) images. We used an image dataset from CPS treated with five different glucose concentrations as input for deep learning models....
A method for delineating traffic low emission control zone based on deep learning and multi-objective optimization.
Environmental monitoring and assessment
Apr 8, 2025
Current methods for defining traffic low emission control zones (TLEZ) often face limitations that hinder their widespread implementation and effectiveness. This study addresses these challenges by employing a comprehensive approach to analyze PM con...
Artificial Intelligence in Dentistry: A Narrative Review of Diagnostic and Therapeutic Applications.
Medical science monitor : international medical journal of experimental and clinical research
Apr 8, 2025
Advancements in digital and precision medicine have fostered the rapid development of artificial intelligence (AI) applications, including machine learning, artificial neural networks (ANN), and deep learning, within the field of dentistry, particula...
Rapid dose prediction for lung CyberKnife radiotherapy plans utilizing a deep learning approach by incorporating dosimetric features delivered by noncoplanar beams.
Biomedical physics & engineering express
Apr 8, 2025
. The dose distribution of lung cancer patients treated with the CyberKnife (CK) system is influenced by various factors, including tumor location and the direction of CK beams. The objective of this study is to present a deep learning approach that ...
Prompting large language models to extract chemical‒disease relation precisely and comprehensively at the document level: an evaluation study.
PloS one
Apr 8, 2025
Given the scarcity of annotated data, current deep learning methods face challenges in the field of document-level chemical-disease relation extraction, making it difficult to achieve precise relation extraction capable of identifying relation types ...
Optimization of shunting operation plan in large freight train depot based on DQN algorithm.
PloS one
Apr 8, 2025
Shunting operation plan is the main daily work of the freight train depot, the optimization of shunting operation plan is of great significance to improve the efficiency of railway operation and production and transportation. In this paper, the deep ...
Year 2023 in Biomedical Natural Language Processing: a Tribute to Large Language Models and Generative AI.
Yearbook of medical informatics
Apr 8, 2025
OBJECTIVES: This synopsis gives insights into scientific publications from 2023 in Natural Language Processing for the biomedical domain. We present the process we followed to identify candidates for NLP's best papers and the two best papers of this ...
A novel intelligent grade classification architecture for Patent Foramen Ovale by Contrast Transthoracic Echocardiography based on deep learning.
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Apr 7, 2025
Patent foramen ovale (PFO) is one of the main causes of ischemic stroke. Due to the complex characteristics of contrast transthoracic echocardiography (cTTE), PFO classification is time-consuming and laborious in clinical practice. For this reason, a...
AI-Driven Detection and Measurement of Keratinized Gingiva in Dental Photographs: Validation Using Reference Retainers.
Journal of clinical periodontology
Apr 7, 2025
AIM: To evaluate a deep learning (DL) model for detecting keratinized gingiva (KG) in dental photographs and validate its clinical applicability using reference retainers for calibration.
Evaluation of Caries Detection on Bitewing Radiographs: A Comparative Analysis of the Improved Deep Learning Model and Dentist Performance.
Journal of esthetic and restorative dentistry : official publication of the American Academy of Esthetic Dentistry ... [et al.]
Apr 7, 2025
OBJECTIVES: The application of deep learning techniques for detecting caries in bitewing radiographs has gained significant attention in recent years. However, the comparative performance of various modern deep learning models and strategies to enhan...
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