AIMC Topic: Deep Learning

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Evaluation of deliverable artificial intelligence-based automated volumetric arc radiation therapy planning for whole pelvic radiation in gynecologic cancer.

Scientific reports
This study aimed to develop a deep learning (DL)-based deliverable whole pelvic volumetric arc radiation therapy (VMAT) for patients with gynecologic cancer using a prototype DL-based automated planning support system, named RatoGuide, to evaluate it...

Deep learning-based classification of coronary arteries and left ventricle using multimodal data for autonomous protocol selection or adjustment in angiography.

Scientific reports
Optimal selection of X-ray imaging parameters is crucial in coronary angiography and structural cardiac procedures to ensure optimal image quality and minimize radiation exposure. These anatomydependent parameters are organized into customizable orga...

Effective reduction of unnecessary biopsies through a deep-learning-assisted aggressive prostate cancer detector.

Scientific reports
Despite being one of the most prevalent cancers, prostate cancer (PCa) shows a significantly high survival rate, provided there is timely detection and treatment. Currently, several screening and diagnostic tests are required to be carried out in ord...

A hybrid deep learning framework for early detection of diabetic retinopathy using retinal fundus images.

Scientific reports
Recent advancements in deep learning have significantly impacted medical image processing domain, enabling sophisticated and accurate diagnostic tools. This paper presents a novel hybrid deep learning framework that combines convolutional neural netw...

A digital photography dataset for Vaccinia Virus plaque quantification using Deep Learning.

Scientific data
Virological plaque assay is the major method of detecting and quantifying infectious viruses in research and diagnostic samples. Furthermore, viral plaque phenotypes contain information about the life cycle and spreading mechanism of the virus formin...

Self-supervised learning for label-free segmentation in cardiac ultrasound.

Nature communications
Segmentation and measurement of cardiac chambers from ultrasound is critical, but laborious and poorly reproducible. Neural networks can assist, but supervised approaches require the same problematic manual annotations. We build a pipeline for self-s...

3D tooth identification for forensic dentistry using deep learning.

BMC oral health
The classification of intraoral teeth structures is a critical component in modern dental analysis and forensic dentistry. Traditional methods, relying on 2D imaging, often suffer from limitations in accuracy and comprehensiveness due to the complex ...

Exploring deep learning in phage discovery and characterization.

Virology
Bacteriophages, or bacterial viruses, play diverse ecological roles by shaping bacterial populations and also hold significant biotechnological and medical potential, including the treatment of infections caused by multidrug-resistant bacteria. The d...

Machine learning and clinical EEG data for multiple sclerosis: A systematic review.

Artificial intelligence in medicine
Multiple Sclerosis (MS) is a chronic neuroinflammatory disease of the Central Nervous System (CNS) in which the body's immune system attacks and destroys the myelin sheath that protects nerve fibers, leading to a wide range of debilitating symptoms a...

The impact of partner interaction on brief social buffering in adolescent female rats as analyzed by deep learning-based object detection algorithms.

Physiology & behavior
Social buffering is a phenomenon whereby the stress response of anyone exposed to a distressing stimulus is alleviated by the presence of conspecific(s). In this study, we aimed to determine whether brief buffering (only 3 min) with conspecific immed...