AIMC Topic: Humans

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Machine learning-based risk factor analysis and prevalence prediction of intestinal parasitic infections using epidemiological survey data.

PLoS neglected tropical diseases
BACKGROUND: Previous epidemiological studies have examined the prevalence and risk factors for a variety of parasitic illnesses, including protozoan and soil-transmitted helminth (STH, e.g., hookworms and roundworms) infections. Despite advancements ...

Maximizing the integration of virtual and experimental screening in hit discovery.

Expert opinion on drug discovery
INTRODUCTION: Experimental and virtual screening contributes to the discovery of more than 50% of clinical candidates. Considering the similar concept and goals, early-phase drug discovery would benefit from the effective integration of these approac...

Artificial intelligence implementation in pancreaticobiliary endoscopy.

Expert review of gastroenterology & hepatology
INTRODUCTION: Artificial intelligence has been rapidly deployed in gastroenterology and endoscopy. The acceleration of deep convolutional neural networks along with hardware development has allowed implementation of artificial intelligence algorithms...

Transformer-Based Deep-Learning Algorithm for Discriminating Demyelinating Diseases of the Central Nervous System With Neuroimaging.

Frontiers in immunology
BACKGROUND: Differential diagnosis of demyelinating diseases of the central nervous system is a challenging task that is prone to errors and inconsistent reading, requiring expertise and additional examination approaches. Advancements in deep-learnin...

Automatic segmentation of multitype retinal fluid from optical coherence tomography images using semisupervised deep learning network.

The British journal of ophthalmology
BACKGROUND/AIMS: To develop and validate a deep learning model for automated segmentation of multitype retinal fluid using optical coherence tomography (OCT) images.

A deep learning network based on multi-scale and attention for the diagnosis of chronic atrophic gastritis.

Zeitschrift fur Gastroenterologie
BACKGROUND AND STUDY AIM: Chronic atrophic gastritis plays an important role in the process of gastric cancer. Deep learning is gradually introduced in the medical field, and how to better apply a convolutional neural network (CNN) to the diagnosis o...

Intelligent and novel multi-type cancer prediction model using optimized ensemble learning.

Computer methods in biomechanics and biomedical engineering
Cancer is known to be highly severe disease and gets incurable even when the treatment has started at the time of diagnosis owing to the occurrence of cancer cells. Diverse machine learning approaches are implemented for predicting the cancer recurre...

EPI phase error correction with deep learning (PEC-DL) at 7 T.

Magnetic resonance in medicine
PURPOSE: The phase mismatch between odd and even echoes in EPI causes Nyquist ghost artifacts. Existing ghost correction methods often suffer from severe residual artifacts and are ineffective with k-space undersampling data. This study proposed a de...

Changes in software as a medical device based on artificial intelligence technologies.

International journal of computer assisted radiology and surgery
PURPOSE: to develop a procedure for registering changes, notifying users about changes made, unifying software as a medical device based on artificial intelligence technologies (SaMD-AI) changes, as well as requirements for testing and inspections-qu...