Machine Learning in Healthcare: Overcoming Challenges and Exploring Future Directions

Ziqin Zhong

2024

Abstract

This paper discusses the application of Machine Learning (ML) in healthcare, focusing on cancer and tumor prediction. This paper also discusses limitations and future prospects. It outlines the ML workflow, which involves data collection, preprocessing, model building, training, and testing. The paper will also mention methods such as Decision Tree and Neural Network. The study reviews current approaches to breast, lung, and brain tumor predictions, highlighting models that integrate clinical data and imaging techniques for improved accuracy. Despite its potential, ML faces challenges such as interpretability, limited applicability across diverse populations, and privacy concerns as these challenges will be dangerous for future use if found. Future prospects include explainable AI techniques like Shapley Additive Explanations (SHAP) and Local Interpretable Model-agnostic Explanations (LIME) for interpretability, transfer learning for adaptability, and federated learning to address privacy issues. These advancements are critical for enhancing the trust, flexibility, and security of ML applications in healthcare.

Paper Citation

in Harvard Style

Zhong Z. (2024). Machine Learning in Healthcare: Overcoming Challenges and Exploring Future Directions. In Proceedings of the 1st International Conference on Modern Logistics and Supply Chain Management - Volume 1: MLSCM; ISBN 978-989-758-738-2, SciTePress, pages 354-357. DOI: 10.5220/0013331100004558

in Bibtex Style

@conference{mlscm24,
author={Ziqin Zhong},
title={Machine Learning in Healthcare: Overcoming Challenges and Exploring Future Directions},
booktitle={Proceedings of the 1st International Conference on Modern Logistics and Supply Chain Management - Volume 1: MLSCM},
year={2024},
pages={354-357},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013331100004558},
isbn={978-989-758-738-2},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 1st International Conference on Modern Logistics and Supply Chain Management - Volume 1: MLSCM
TI - Machine Learning in Healthcare: Overcoming Challenges and Exploring Future Directions
SN - 978-989-758-738-2
AU - Zhong Z.
PY - 2024
SP - 354
EP - 357
DO - 10.5220/0013331100004558
PB - SciTePress