AIMC Topic: Deep Learning

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Image segmentation of impacted mesiodens using deep learning.

The Journal of clinical pediatric dentistry
This study aimed to evaluate the performance of deep learning algorithms for the classification and segmentation of impacted mesiodens in pediatric panoramic radiographs. A total of 850 panoramic radiographs of pediatric patients (aged 3-9 years) was...

Artificial intelligence in coronary artery calcium score: rationale, different approaches, and outcomes.

The international journal of cardiovascular imaging
Almost 35 years after its introduction, coronary artery calcium score (CACS) not only survived technological advances but became one of the cornerstones of contemporary cardiovascular imaging. Its simplicity and quantitative nature established it as ...

Deep Learning Bridged Bioactivity, Structure, and GC-HRMS-Readable Evidence to Decipher Nontarget Toxicants in Sediments.

Environmental science & technology
Identifying causative toxicants in mixtures is critical, but this task is challenging when mixtures contain multiple chemical classes. Effect-based methods are used to complement chemical analyses to identify toxicants, yet conventional bioassays typ...

BraNet: a mobil application for breast image classification based on deep learning algorithms.

Medical & biological engineering & computing
Mobile health apps are widely used for breast cancer detection using artificial intelligence algorithms, providing radiologists with second opinions and reducing false diagnoses. This study aims to develop an open-source mobile app named "BraNet" for...

Adversarial attacks and adversarial training for burn image segmentation based on deep learning.

Medical & biological engineering & computing
Deep learning has been widely applied in the fields of image classification and segmentation, while adversarial attacks can impact the model's results in image segmentation and classification. Especially in medical images, due to constraints from fac...

An automated approach for real-time informative frames classification in laryngeal endoscopy using deep learning.

European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery
PURPOSE: Informative image selection in laryngoscopy has the potential for improving automatic data extraction alone, for selective data storage and a faster review process, or in combination with other artificial intelligence (AI) detection or diagn...

Artificial intelligence in colonoscopy: from detection to diagnosis.

The Korean journal of internal medicine
This study reviews the recent progress of artificial intelligence for colonoscopy from detection to diagnosis. The source of data was 27 original studies in PubMed. The search terms were "colonoscopy" (title) and "deep learning" (abstract). The eligi...

A deep-learning-based scatter correction with water equivalent path length map for digital radiography.

Radiological physics and technology
We proposed a new deep learning (DL) model for accurate scatter correction in digital radiography. The proposed network featured a pixel-wise water equivalent path length (WEPL) map of subjects with diverse sizes and 3D inner structures. The proposed...

A hybrid framework for glaucoma detection through federated machine learning and deep learning models.

BMC medical informatics and decision making
BACKGROUND: Glaucoma, the second leading cause of global blindness, demands timely detection due to its asymptomatic progression. This paper introduces an advanced computerized system, integrates Machine Learning (ML), convolutional neural networks (...

Survival estimation of oral cancer using fuzzy deep learning.

BMC oral health
BACKGROUND: Oral cancer is a deadly disease and a major cause of morbidity and mortality worldwide. The purpose of this study was to develop a fuzzy deep learning (FDL)-based model to estimate the survival time based on clinicopathologic data of oral...