Machine Learning Approaches: Detecting the Disease Variants in Human-Exhaled Breath Biomarkers-Reference-Cited by-同舟云学术

Machine Learning Approaches: Detecting the Disease Variants in Human-Exhaled Breath Biomarkers

Published:2023-12-22 Issue:1 Volume:9 Page:215-226
ISSN:2470-1343
Container-title:ACS Omega
language:en
Short-container-title:ACS Omega

Author:

Selvaraj Bhuvaneswari¹²,Rajasekar Elakkiya³,Balaguru Rayappan John Bosco¹²^ORCID

Affiliation:

1. Centre for Nanotechnology & Advanced Biomaterials (CeNTAB), SASTRA Deemed University, Thanjavur, Tamil Nadu 613 401, India

2. School of Electrical & Electronics Engineering, SASTRA Deemed University, Thanjavur, Tamil Nadu 613 401, India

3. Department of Computer Science, Birla Institute of Technology & Science, Pilani Dubai Campus, Dubai International Academic City, Dubai 345055, United Arab Emirates

Funder

Science and Engineering Research Board

Publisher

American Chemical Society (ACS)

Subject

General Chemical Engineering,General Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acsomega.3c03755

Reference34 articles.

1. Electronic noses and disease diagnostics

2. Advances in Electronic-Nose Technologies Developed for Biomedical Applications

3. The use of Big Data Analytics in healthcare

4. Al-Masri, S.; Safi, A.; El-Farra, A. A. H.; Shehada, M. Designing a Biosignal Extraction Device for Measuring a Blood Pressure. In 2018 International Conference on Promising Electronic Technologies (ICPET); IEEE, 2018; pp 108–112.

5. Big data analytics for preventive medicine

Cited by 1 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. Development of polyimide nanofiber aerogels with a 3D multi-level pore structure: A new sensor for colorimetric detection of breath acetone;Chemical Engineering Journal;2024-09