AIMC Topic: Deep Learning

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Monitoring of granite quarries using deep learning and UAV photogrammetry in Bengaluru, India.

PloS one
Granite quarrying, a cornerstone of the construction industry in South India, yields significant economic benefits but poses substantial environmental and social challenges, including land degradation, dust pollution, alternation of the water regime,...

Broad-spectrum eye disease classification using a deep learning-based tailored software lens.

PloS one
The early and accurate classification of eye diseases is essential for preventing irreversible visual impairment. This task can be performed by deep learning approaches that automatically classify retinal fundus images according to potential illnesse...

Impact of blood culture positivity at intensive care unit admission on mortality in infective endocarditis: Machine learning and deep learning-based causal inference models.

PloS one
BACKGROUND: Infective endocarditis (IE) carries high in-hospital mortality, particularly among intensive care unit (ICU) patients. The predictive role of blood culture positivity in these patients remains unclear.

Towards better Hebrew clickbait detection: Insights from BERT and data augmentation.

PloS one
Clickbait headlines, designed to entice readers with sensationalized or misleading content, pose significant challenges in the digital landscape. They exploit curiosity to generate traffic and revenue, often at the cost of spreading misinformation an...

Multi-Regional deep learning models for identifying dental restorations and prosthesis in panoramic radiographs.

BMC oral health
BACKGROUND: This study introduces a novel deep learning methodology for the automated detection of a wide range of dental prostheses, including crowns, bridges, and implants, as well as various dental treatments such as fillings, root canal therapies...

Unveiling the role of harmonization on clinically significant prostate cancer detection using MRI.

Scientific reports
Accurate detection and classification of clinically significant prostate cancer remain critical challenges in medical imaging. Despite numerous studies focusing on feature extraction and classification, none have systematically assessed the impact of...

Hierarchical attention mechanism combined with deep neural networks for accurate semantic segmentation of dental structures in panoramic radiographs.

Scientific reports
Computer vision, a rapidly advancing branch of artificial intelligence (AI), has gained significant attention in medical and dental applications. Semantic segmentation, a key technique within computer vision, enables the precise identification and de...

FastKAN-DDD: A novel fast Kolmogorov-Arnold network-based approach for driver drowsiness detection optimized for TinyML deployment.

PloS one
Driver drowsiness is a leading cause of traffic accidents and fatalities, highlighting the urgent need for intelligent systems capable of real-time fatigue detection. Although recent advancements in machine learning (ML) and deep learning (DL) have s...

Deep learning-based automated detection of supernumerary teeth in pediatric panoramic radiographs.

PloS one
INTRODUCTION: Supernumerary teeth are a common developmental anomaly in pediatric patients, potentially leading to complications such as impaction, crowding, and delayed eruption. Accurate and early detection is critical to prevent these sequelae and...

Interpretable weakly-supervised learning through kernel density matrices: A digital pathology use case.

PloS one
Classification methods based on deep learning require selecting between fully-supervised or weakly-supervised approaches, each presenting limitations in uncertainty quantification and interpretability. A framework unifying both supervision modes whil...