AIMC Topic: Humans

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Novel deep neural network architecture fusion to simultaneously predict short-term and long-term energy consumption.

PloS one
Energy is integral to the socio-economic development of every country. This development leads to a rapid increase in the demand for energy consumption. However, due to the constraints and costs associated with energy generation resources, it has beco...

ChatGPT-4o can serve as the second rater for data extraction in systematic reviews.

PloS one
BACKGROUND: Systematic reviews provide clarity of a bulk of evidence and support the transfer of knowledge from clinical trials to guidelines. Yet, they are time-consuming. Artificial intelligence (AI), like ChatGPT-4o, may streamline processes of da...

Accurate multi-behavior sequence-aware recommendation via graph convolution networks.

PloS one
How can we recommend items to users utilizing multiple types of user behavior data? Multi-behavior recommender systems leverage various types of user behavior data to enhance recommendation performance for the target behavior. These systems aim to pr...

Fault tolerance in distributed systems using deep learning approaches.

PloS one
Recently, distributed systems have become the backbone of technological development. It serves as the foundation for new trends technologies such as blockchain, the internet of things and others. A distributed system provides fault tolerance and dece...

Deep learning-based differential gut flora for prediction of Parkinson's.

PloS one
BACKGROUND: There had been extensive research on the role of the gut microbiota in human health and disease. Increasing evidence suggested that the gut-brain axis played a crucial role in Parkinson's disease, with changes in the gut microbiota specul...

Uncertainty Global Contrastive Learning Framework for Semi-Supervised Medical Image Segmentation.

IEEE journal of biomedical and health informatics
In semi-supervised medical image segmentation, the issue of fuzzy boundaries for segmented objects arises. With limited labeled data and the interaction of boundaries from different segmented objects, classifying segmentation boundaries becomes chall...

HepNet: Deep Neural Network for Classification of Early-Stage Hepatic Steatosis Using Microwave Signals.

IEEE journal of biomedical and health informatics
Hepatic steatosis, a key factor in chronic liver diseases, is difficult to diagnose early. This study introduces a classifier for hepatic steatosis using microwave technology, validated through clinical trials. Our method uses microwave signals and d...

rU-Net, Multi-Scale Feature Fusion and Transfer Learning: Unlocking the Potential of Cuffless Blood Pressure Monitoring With PPG and ECG.

IEEE journal of biomedical and health informatics
This study introduces an innovative deep-learning model for cuffless blood pressure estimation using PPG and ECG signals, demonstrating state-of-the-art performance on the largest clean dataset, PulseDB. The rU-Net architecture, a fusion of U-Net and...

mDARTS: Searching ML-Based ECG Classifiers Against Membership Inference Attacks.

IEEE journal of biomedical and health informatics
This paper addresses the critical need for elctrocardiogram (ECG) classifier architectures that balance high classification performance with robust privacy protection against membership inference attacks (MIA). We introduce a comprehensive approach t...

Facial Expression Recognition for Healthcare Monitoring Systems Using Neural Random Forest.

IEEE journal of biomedical and health informatics
Facial expressions vary with different health conditions, making a facial expression recognition (FER) system valuable within a healthcare framework. Achieving accurate recognition of facial expressions is a considerable challenge due to the difficul...