AIMC Topic: Humans

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Cooperative Learning for Personalized Context-Aware Pain Assessment From Wearable Data.

IEEE journal of biomedical and health informatics
Despite the promising performance of automated pain assessment methods, current methods suffer from performance generalization due to the lack of relatively large, diverse, and annotated pain datasets. Further, the majority of current methods do not ...

Heterogeneous Collaborative Learning for Personalized Healthcare Analytics via Messenger Distillation.

IEEE journal of biomedical and health informatics
The Healthcare Internet-of-Things (IoT) framework aims to provide personalized medical services with edge devices. Due to the inevitable data sparsity on an individual device, cross-device collaboration is introduced to enhance the power of distribut...

Extensive clinical testing of Deep Learning Segmentation models for thorax and breast cancer radiotherapy planning.

Acta oncologica (Stockholm, Sweden)
BACKGROUND: The performance of deep learning segmentation (DLS) models for automatic organ extraction from CT images in the thorax and breast regions was investigated. Furthermore, the readiness and feasibility of integrating DLS into clinical practi...

Machine learning-based classification analysis of knowledge worker mental stress.

Frontiers in public health
The aim of this study is to analyze the performance of classifying stress and non-stress by measuring biosignal data using a wearable watch without interfering with work activities at work. An experiment is designed where participants wear a Galaxy W...

Deep learning-based age estimation from clinical Computed Tomography image data of the thorax and abdomen in the adult population.

PloS one
Aging is an important risk factor for disease, leading to morphological change that can be assessed on Computed Tomography (CT) scans. We propose a deep learning model for automated age estimation based on CT- scans of the thorax and abdomen generate...

A framework for integrating artificial intelligence for clinical care with continuous therapeutic monitoring.

Nature biomedical engineering
The complex relationships between continuously monitored health signals and therapeutic regimens can be modelled via machine learning. However, the clinical implementation of the models will require changes to clinical workflows. Here we outline Clin...

A deep learning-based approach for distinguishing different stress levels of human brain using EEG and pulse rate.

Computer methods in biomechanics and biomedical engineering
In today's world, people suffer from many fatal maladies, and stress is one of them. Excessive stress can have deleterious effects on the health, brain, mind, and nervous system of humans. The goal of this paper is to design a deep learningbased huma...

Enhancing human-AI collaboration: The case of colonoscopy.

Digestive and liver disease : official journal of the Italian Society of Gastroenterology and the Italian Association for the Study of the Liver
Diagnostic errors impact patient health and healthcare costs. Artificial Intelligence (AI) shows promise in mitigating this burden by supporting Medical Doctors in decision-making. However, the mere display of excellent or even superhuman performance...

A comprehensive segmentation of chest X-ray improves deep learning-based WHO radiologically confirmed pneumonia diagnosis in children.

European radiology
OBJECTIVES: To investigate a comprehensive segmentation of chest X-ray (CXR) in promoting deep learning-based World Health Organization's (WHO) radiologically confirmed pneumonia diagnosis in children.