Artificial Intelligence (AI) and Machine Learning (ML) for Latest Trends in Biosensing Applications
Artificial intelligence, Machine learning, Biosensor network, Wearable biosensors, Deep learning, Support Vector Machine
Biosensors are becoming more popular as analytical tools based to their ability to detect and identify biological substances in a variety of applications. Biosensors have proven useful in many important fields such as medicine, food safety, environmental monitoring, security, medicine and verification. One of the leaders in the biosensor market is diagnostic equipment, as diagnostic equipment supports approximately 70% of medical decisions. This article explains on the use of artificial intelligence (AI) and machine learning (ML) in various types of biosensors. Artificial intelligence increases the capabilities of biosensors and is used in automation, electronics, medical devices, etc. It opens up new opportunities in fields. Wearable biosensors are now entering our daily lives and playing an important role in the advancement of technology. Biosensors with micro-nano structure have advantages such as small size, high sensitivity, production, simple arrangement and integration compared to chemical biosensors, and these advantages make them an improved method for pressure sensors. In this article, we review recent advances in machine learning for biosensor applications. We discuss various machine learning techniques applied to biosensors, including models for data processing, feature extraction, classification, and data analysis. Issues related to machine learning and biosensor integration are also touched upon and future trends in this field are presented.
"Artificial Intelligence (AI) and Machine Learning (ML) for Latest Trends in Biosensing Applications", IJSDR - International Journal of Scientific Development and Research (www.IJSDR.org), ISSN:2455-2631, Vol.8, Issue 10, page no.388 - 399, October-2023, Available :https://ijsdr.org/papers/IJSDR2310067.pdf
Volume 8
Issue 10,
October-2023
Pages : 388 - 399
Paper Reg. ID: IJSDR_208941
Published Paper Id: IJSDR2310067
Downloads: 000347335
Research Area: Engineering
Country: Bangalore, Karnataka, India
ISSN: 2455-2631 | IMPACT FACTOR: 9.15 Calculated By Google Scholar | ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.15 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publisher: IJSDR(IJ Publication) Janvi Wave
