AIMC Topic: Humans

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Explainable AI based automated segmentation and multi-stage classification of gastroesophageal reflux using machine learning techniques.

Biomedical physics & engineering express
Presently, close to two million patients globally succumb to gastrointestinal reflux diseases (GERD). Video endoscopy represents cutting-edge technology in medical imaging, facilitating the diagnosis of various gastrointestinal ailments including sto...

Training immunophenotyping deep learning models with the same-section ground truth cell label derivation method improves virtual staining accuracy.

Frontiers in immunology
INTRODUCTION: Deep learning (DL) models predicting biomarker expression in images of hematoxylin and eosin (H&E)-stained tissues can improve access to multi-marker immunophenotyping, crucial for therapeutic monitoring, biomarker discovery, and person...

Research on the evaluation and impact trends of China's skill talent ecosystem in the digital era - An analysis based on neural network models and PVAR models.

PloS one
This study develops a "Skill Talent Ecological Evaluation Model" across cultivation, potential energy, kinetic energy, innovation, and service and support ecologies. AHP-entropy determines indicator weights, Hopfield neural network assesses talent ec...

The analysis of the internet of things database query and optimization using deep learning network model.

PloS one
To explore the application effect of the deep learning (DL) network model in the Internet of Things (IoT) database query and optimization. This study first analyzes the architecture of IoT database queries, then explores the DL network model, and fin...

HOTSPOT: An ad hoc teamwork platform for mixed human-robot teams.

PloS one
Ad hoc teamwork is a research topic in multi-agent systems whereby an agent (the "ad hoc agent") must successfully collaborate with a set of unknown agents (the "teammates") without any prior coordination or communication protocol. However, research ...

Exploring the diagnostic performance of machine learning in prediction of metabolic phenotypes focusing on thyroid function.

PloS one
In this study, we employed various machine learning models to predict metabolic phenotypes, focusing on thyroid function, using a dataset from the National Health and Nutrition Examination Survey (NHANES) from 2007 to 2012. Our analysis utilized labo...

Recognition of Patient Gender: A Machine Learning Preliminary Analysis Using Heart Sounds from Children and Adolescents.

Pediatric cardiology
Research has shown that X-rays and fundus images can classify gender, age group, and race, raising concerns about bias and fairness in medical AI applications. However, the potential for physiological sounds to classify sociodemographic traits has no...

Estimating substance use disparities across intersectional social positions using machine learning: An application of group-lasso interaction network.

Psychology of addictive behaviors : journal of the Society of Psychologists in Addictive Behaviors
OBJECTIVE: An aim of quantitative intersectional research is to model the joint impact of multiple social positions on health risk behaviors. Although moderated multiple regression is frequently used to pursue intersectional research hypotheses, such...