Machine Learning, Deep Learning and Image Processing for Healthcare: A Crux for Detection and Prediction of Disease
Author:
Publisher
Springer Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-16-6285-0_25
Reference68 articles.
1. Jordan MI, Mitchell MT (2015) Machine learning: a review. Machine learning: trends, perspectives, and prospects. Science 349(6245):255–260
2. Pavlopoulos SA (1999) Designing and implementing the transition to a fully digital hospital. IEEE Trans Inf Technol Biomed 3(1):6–19
3. Bazazeh D (2016) Comparative study of machine learning algorithms for breast cancer detection and diagnosis. In: 5th International conference on electronic devices, systems and applications (ICEDSA)
4. Pires NM (2016) Highly sensitive detection of human cancer antigens by an immunogold-silver assay chip coupled with a polythiophene-based optical sensor. In: 38th Annual International conference of the IEEE engineering in medicine and biology society (EMB)
5. Peng C (2020) Cardiovascular diseases prediction using artificial neural networks: a survey. In: IEEE 2nd Eurasia conference on biomedical engineering, healthcare and sustainability (ECBIOS)
Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. Optimizing protein sequence classification: integrating deep learning models with Bayesian optimization for enhanced biological analysis;BMC Medical Informatics and Decision Making;2024-08-27
2. Consumer electronics based smart technologies for enhanced terahertz healthcare having an integration of split learning with medical imaging;Scientific Reports;2024-05-06
3. Machine Learning-Enabled Medical Image Analysis for Disease Detection in the Cloud;2023 International Conference on Artificial Intelligence for Innovations in Healthcare Industries (ICAIIHI);2023-12-29
4. Algorithmic Insights into Predicting Hypertension Using Health Data in Cloud-Based Environments;2023 International Conference on Artificial Intelligence for Innovations in Healthcare Industries (ICAIIHI);2023-12-29
1.学者识别学者识别
2.学术分析学术分析
3.人才评估人才评估
"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370
www.globalauthorid.com
TOP
Copyright © 2019-2024 北京同舟云网络信息技术有限公司 京公网安备11010802033243号 京ICP备18003416号-3