AIMC Topic: Deep Learning

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DrugGen enhances drug discovery with large language models and reinforcement learning.

Scientific reports
Traditional drug design faces significant challenges due to inherent chemical and biological complexities, often resulting in high failure rates in clinical trials. Deep learning advancements, particularly generative models, offer potential solutions...

Stigmatisation of gambling disorder in social media: a tailored deep learning approach for YouTube comments.

Harm reduction journal
BACKGROUND: The stigmatisation of gamblers, particularly those with a gambling disorder, and self-stigmatisation are considered substantial barriers to seeking help and treatment. To develop effective strategies to reduce the stigma associated with g...

Decoding Recurrence in Early-Stage and Locoregionally Advanced Non-Small Cell Lung Cancer: Insights From Electronic Health Records and Natural Language Processing.

JCO clinical cancer informatics
PURPOSE: Recurrences after curative resection in early-stage and locoregionally advanced non-small cell lung cancer (NSCLC) are common, necessitating a nuanced understanding of associated risk factors. This study aimed to establish a natural language...

DWI of the rectum with deep learning reconstruction: comparison of PROPELLER, reduced FOV, and conventional DWI.

Abdominal radiology (New York)
PURPOSE: To compare the image quality and diagnostic performance of periodically rotated overlapping parallel lines with enhanced reconstruction (PROPELLER), reduced field-of-view (rFOV), and conventional diffusion-weighted imaging (cDWI) combined wi...

Convolutional Neural Network approach to classify mitochondrial morphologies.

Computational biology and chemistry
The morphology of the mitochondrial network is a major indicator of cellular health and function, with changes often linked to various physiological and pathological conditions. As a result, efficient methods to quickly assess mitochondrial shape in ...

Multi-modal multi-task deep neural networks for sleep disordered breathing assessment using cardiac and audio signals.

International journal of medical informatics
BACKGROUND AND OBJECTIVE: Sleep disordered breathing (SDB) is one of the most common sleep disorders and has short-term consequences for daytime functioning while being a risk factor for several conditions, such as cardiovascular disease. Polysomnogr...

Deep learning algorithms to assist in imaging diagnosis in individuals with disc herniation or spondylolisthesis: A scoping review.

International journal of medical informatics
BACKGROUND: Deep learning applications in medical imaging have advanced significantly, supporting the diagnosis of spinal disorders such as disc herniation and spondylolisthesis. This study aimed to review deep learning algorithms used in diagnostic ...

Adaptive token selection for scalable point cloud transformers.

Neural networks : the official journal of the International Neural Network Society
The recent surge in 3D data acquisition has spurred the development of geometric deep learning models for point cloud processing, boosted by the remarkable success of transformers in natural language processing. While point cloud transformers (PTs) h...

EffiCOVID-net: A highly efficient convolutional neural network for COVID-19 diagnosis using chest X-ray imaging.

Methods (San Diego, Calif.)
The global COVID-19 pandemic has drastically affected daily life, emphasizing the urgent need for early and accurate detection to provide adequate medical treatment, especially with limited antiviral options. Chest X-ray imaging has proven crucial fo...

Fully Automated Online Adaptive Radiation Therapy Decision-Making for Cervical Cancer Using Artificial Intelligence.

International journal of radiation oncology, biology, physics
BACKGROUND: Interfraction variations during radiation therapy pose a challenge for patients with cervical cancer, highlighting the benefits of online adaptive radiation therapy (oART). However, adaptation decisions rely on subjective image reviews by...