AIMC Topic: Deep Learning

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Predicting the Utility of Scientific Articles for Emerging Pandemics Using Their Titles and Natural Language Processing.

Disaster medicine and public health preparedness
OBJECTIVE: Not all scientific publications are equally useful to policy-makers tasked with mitigating the spread and impact of diseases, especially at the start of novel epidemics and pandemics. The urgent need for actionable, evidence-based informat...

Whole-body magnetic resonance imaging at 0.05 Tesla.

Science (New York, N.Y.)
Despite a half-century of advancements, global magnetic resonance imaging (MRI) accessibility remains limited and uneven, hindering its full potential in health care. Initially, MRI development focused on low fields around 0.05 Tesla, but progress ha...

Predicting drug-Protein interaction with deep learning framework for molecular graphs and sequences: Potential candidates against SAR-CoV-2.

PloS one
The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) caused the COVID-19 disease, which represents a new life-threatening disaster. Regarding viral infection, many therapeutics have been investigated to alleviate the epidemiology such as ...

Deep learning-based detection of irreversible pulpitis in primary molars.

International journal of paediatric dentistry
BACKGROUND: Changes in healthy and inflamed pulp on periapical radiographs are traditionally so subtle that they may be imperceptible to human experts, limiting its potential use as an adjunct clinical diagnostic feature.

Finding and following: a deep learning-based pipeline for tracking platelets during thrombus formation and .

Platelets
The last decade has seen increasing use of advanced imaging techniques in platelet research. However, there has been a lag in the development of image analysis methods, leaving much of the information trapped in images. Herein, we present a robust an...

Assessing deep learning reconstruction for faster prostate MRI: visual vs. diagnostic performance metrics.

European radiology
OBJECTIVE: Deep learning (DL) MRI reconstruction enables fast scan acquisition with good visual quality, but the diagnostic impact is often not assessed because of large reader study requirements. This study used existing diagnostic DL to assess the ...

Comparison of deep learning models to traditional Cox regression in predicting survival of colon cancer: Based on the SEER database.

Journal of gastroenterology and hepatology
BACKGROUND AND AIM: In this study, a deep learning algorithm was used to predict the survival rate of colon cancer (CC) patients, and compared its performance with traditional Cox regression.

Patient's airway monitoring during cardiopulmonary resuscitation using deep networks.

Medical engineering & physics
Cardiopulmonary resuscitation (CPR) is a crucial life-saving technique commonly administered to individuals experiencing cardiac arrest. Among the important aspects of CPR is ensuring the correct airway position of the patient, which is typically mon...

Real-time coronary artery segmentation in CAG images: A semi-supervised deep learning strategy.

Artificial intelligence in medicine
BACKGROUND: When treating patients with coronary artery disease and concurrent renal concerns, we often encounter a conundrum: how to achieve a clearer view of vascular details while minimizing the contrast and radiation doses during percutaneous cor...

CancerGATE: Prediction of cancer-driver genes using graph attention autoencoders.

Computers in biology and medicine
Discovery of the cancer type specific-driver genes is important for understanding the molecular mechanisms of each cancer type and for providing proper treatment. Recently, graph deep learning methods became widely used in finding cancer-driver genes...