AIMC Topic: Humans

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Validation and Improvement of a Convolutional Neural Network to Predict the Involved Pathology in a Head and Neck Surgery Cohort.

International journal of environmental research and public health
The selection of patients for the constitution of a cohort is a major issue for clinical research (prospective studies and retrospective studies in real life). Our objective was to validate in real life conditions the use of a Deep Learning process b...

Estimating individual treatment effect on disability progression in multiple sclerosis using deep learning.

Nature communications
Disability progression in multiple sclerosis remains resistant to treatment. The absence of a suitable biomarker to allow for phase 2 clinical trials presents a high barrier for drug development. We propose to enable short proof-of-concept trials by ...

General object-based features account for letter perception.

PLoS computational biology
After years of experience, humans become experts at perceiving letters. Is this visual capacity attained by learning specialized letter features, or by reusing general visual features previously learned in service of object categorization? To explore...

Deep learning techniques for detecting and recognizing face masks: A survey.

Frontiers in public health
The year 2020 brought many changes to the lives of people all over the world with the outbreak of COVID-19; we saw lockdowns for months and deaths of many individuals, which set the world economy back miles. As research was conducted to create vaccin...

Application of supervised machine learning algorithms to predict the risk of hidden blood loss during the perioperative period in thoracolumbar burst fracture patients complicated with neurological compromise.

Frontiers in public health
BACKGROUND: Machine learning (ML) is a type of artificial intelligence (AI) and has been utilized in clinical research and practice to construct high-performing prediction models. Hidden blood loss (HBL) is prevalent during the perioperative period o...

Strategies for Ideological and Political Education in Colleges and Universities Based on Deep Learning.

Computational intelligence and neuroscience
Ideological and political education in colleges and universities is routinely burdened with the job of building morality and cultivating people, which is related to the cultivation of college students' ideals and beliefs, spiritual pursuits, and poli...

Construction of College Chinese Blended Teaching Mode Based on Decision Tree Classification Model in New Media Context.

Computational intelligence and neuroscience
Based on the context of new media and big data, this article uses the decision tree classification model to construct the college Chinese hybrid teaching mode. In order to verify the accuracy of ID3 algorithm prediction, the comparison of the ID3 alg...

Primary Investigation of Deep Learning Models for Japanese "Group Classification" of Whole-Slide Images of Gastric Endoscopic Biopsy.

Computational and mathematical methods in medicine
BACKGROUND: Accurate pathological diagnosis of gastric endoscopic biopsy could greatly improve the opportunity of early diagnosis and treatment of gastric cancer. The Japanese "Group classification" of gastric biopsy corresponds well with the endosco...

Predictive Models for Knee Pain in Middle-Aged and Elderly Individuals Based on Machine Learning Methods.

Computational and mathematical methods in medicine
AIM: This study used machine learning methods to develop a prediction model for knee pain in middle-aged and elderly individuals.

Superlative Feature Selection Based Image Classification Using Deep Learning in Medical Imaging.

Journal of healthcare engineering
Medical image recognition plays an essential role in the forecasting and early identification of serious diseases in the field of identification. Medical pictures are essential to a patient's health record since they may be used to control, manage, a...