Examining the Role of Machine Learning and Artificial Intelligence in the Advancement of Bioanalytical Techniques for Data Interpretation
Received Date: Mar 01, 2025 / Published Date: Mar 28, 2025
Abstract
The rapid evolution of bioanalytical techniques has generated vast datasets from complex biological systems, posing significant challenges for data interpretation. Machine learning (ML) and artificial intelligence (AI) have emerged as pivotal tools in addressing these challenges, enhancing the accuracy, speed, and scalability of bioanalytical methods such as mass spectrometry, next-generation sequencing, and biosensor assays. This article explores how ML and AI are transforming data interpretation in bioanalysis by automating pattern recognition, improving predictive modeling, and enabling real-time analysis. Through case studies and recent advancements, it highlights their contributions to biomarker discovery, disease diagnostics, and personalized medicine, while also addressing limitations and future directions. The integration of AI and ML into bioanalytical workflows promises to unlock deeper insights into biological processes, revolutionizing modern science and healthcare
Citation: Anika D (2025) Examining the Role of Machine Learning and Artificial Intelligence in the Advancement of Bioanalytical Techniques for Data Interpretation. J Anal Bioanal Tech 16: 739. Doi: 10.4172/2155-9872.1000739
Copyright: © 2025 Anika D. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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