Intelligent Healthcare with Federated Learning: A Brief Investigation

Hengjie Ma

2024

Abstract

Intelligent healthcare is an emerging field that leverages technologies such as wearable Internet of Things (IoT) devices and deep learning to analyze various types of medical data, including traditional records, medical images, and sensor data from wearables. These innovations facilitate more accurate diagnosis and personalized treatment. However, they also raise significant privacy concerns, as sensitive data collected from devices like smart speakers and IoT wearables may be vulnerable to breaches. Federated Learning (FL) offers a promising solution by allowing data to remain on local devices while sharing only model updates with a central server. This method enhances privacy and reduces the risks associated with transferring personal medical data. This paper summarizes some of the recent research outcomes in this field, including a brief introduction to the federated learning algorithm and its variants, a privacy-preserved medical data processing model SCALT, different FL-IoMT architectures according to data partition, a clustered federated learning based multimodal COVID-19 diagnosis model and voice recognition-based Alzheimer’s disease detection ADDetector. However, challenges such as data heterogeneity and hardware limitations remain, requiring further algorithmic improvements and specialized hardware development. As FL holds the potential to revolutionize healthcare, enabling safer, more efficient processing of medical data while protecting patient privacy, this paper gives this brief review to investigate the current outcomes of this field and gives out.

Paper Citation

in Harvard Style

Ma H. (2024). Intelligent Healthcare with Federated Learning: A Brief Investigation. In Proceedings of the 2nd International Conference on Data Analysis and Machine Learning - Volume 1: DAML; ISBN 978-989-758-754-2, SciTePress, pages 516-520. DOI: 10.5220/0013527500004619

in Bibtex Style

@conference{daml24,
author={Hengjie Ma},
title={Intelligent Healthcare with Federated Learning: A Brief Investigation},
booktitle={Proceedings of the 2nd International Conference on Data Analysis and Machine Learning - Volume 1: DAML},
year={2024},
pages={516-520},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013527500004619},
isbn={978-989-758-754-2},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 2nd International Conference on Data Analysis and Machine Learning - Volume 1: DAML
TI - Intelligent Healthcare with Federated Learning: A Brief Investigation
SN - 978-989-758-754-2
AU - Ma H.
PY - 2024
SP - 516
EP - 520
DO - 10.5220/0013527500004619
PB - SciTePress