AIMC Topic: Deep Learning

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Unveiling Thymoma Typing Through Hyperspectral Imaging and Deep Learning.

Journal of biophotonics
Thymoma, a rare tumor from thymic epithelial cells, presents diagnostic challenges because of the subjective nature of traditional methods, leading to high false-negative rates and long diagnosis times. This study introduces a thymoma classification ...

Video-audio neural network ensemble for comprehensive screening of autism spectrum disorder in young children.

PloS one
A timely diagnosis of autism is paramount to allow early therapeutic intervention in preschoolers. Deep Learning tools have been increasingly used to identify specific autistic symptoms. But they also offer opportunities for broad automated detection...

Design of image segmentation model based on residual connection and feature fusion.

PloS one
With the development of deep learning technology, convolutional neural networks have made great progress in the field of image segmentation. However, for complex scenes and multi-scale target images, the existing technologies are still unable to achi...

Machine learning and deep learning-based approach to categorize Bengali comments on social networks using fused dataset.

PloS one
Through the advancement of the contemporary web and the rapid adoption of social media platforms such as YouTube, Twitter, and Facebook, for example, life has become much easier when dealing with certain highly personal problems. The far-reaching con...

Artificial neural networks development in prosthodontics - a systematic mapping review.

Journal of dentistry
OBJECTIVES: This study aimed to systematically categorize the available literature and offer a comprehensive overview of artificial neural network (ANN) prediction models in prosthodontics. Specifically, the present research introduces a systematic a...

Uncertainty-aware probabilistic graph neural networks for road-level traffic crash prediction.

Accident; analysis and prevention
Traffic crashes present substantial challenges to human safety and socio-economic development in urban areas. Developing a reliable and responsible traffic crash prediction model is crucial to address growing public safety concerns and improve the sa...

Accelerated 2D radial Look-Locker T1 mapping using a deep learning-based rapid inversion recovery sampling technique.

NMR in biomedicine
Efficient abdominal coverage with T1-mapping methods currently available in the clinic is limited by the breath hold period (BHP) and the time needed for T1 recovery. This work develops a T1-mapping framework for efficient abdominal coverage based on...

Deep Reinforcement Learning for personalized diagnostic decision pathways using Electronic Health Records: A comparative study on anemia and Systemic Lupus Erythematosus.

Artificial intelligence in medicine
BACKGROUND: Clinical diagnoses are typically made by following a series of steps recommended by guidelines that are authored by colleges of experts. Accordingly, guidelines play a crucial role in rationalizing clinical decisions. However, they suffer...

Diagnosis and Screening of Velocardiofacial Syndrome by Evaluating Facial Photographs Using a Deep Learning-Based Algorithm.

Plastic and reconstructive surgery
BACKGROUND: Early detection of rare genetic diseases, including velocardiofacial syndrome (VCFS), is essential for patient well-being. However, the rarity of these diseases and limited clinical experience of physicians make diagnosis challenging. Dee...

MobileNet-V2: An Enhanced Skin Disease Classification by Attention and Multi-Scale Features.

Journal of imaging informatics in medicine
The increasing prevalence of skin diseases necessitates accurate and efficient diagnostic tools. This research introduces a novel skin disease classification model leveraging advanced deep learning techniques. The proposed architecture combines the M...