Recent Advances in Electrochemical Biosensors: Applications, Challenges, and Future Scope

Area of Science:

• Electrochemistry
• Biosensor Technology
• Biomedical Diagnostics

Background:

• Electrochemical biosensors convert biological signals into electrical outputs.
• They are crucial for detecting biomarkers in diverse samples like sweat and blood.
• Effective biosensor performance relies on immobilization techniques and transducers.

Purpose of the Study:

• To review different types of electrochemical biosensors and their applications.
• To highlight the benefits of machine learning in biosensing.
• To identify challenges and future directions in electrochemical biosensor development.

Main Methods:

• Literature review of electrochemical biosensors.
• Analysis of machine learning applications in biosensing.
• Discussion of current challenges and knowledge gaps.

Main Results:

• Electrochemical biosensors have broad applications in medicine, food, and defense.
• Machine learning aids in interpreting large datasets and mitigating impurity interference.
• Integration of ML improves biosensor sensitivity and data analysis.

Conclusions:

• Electrochemical biosensors are promising diagnostic tools.
• Machine learning is essential for advancing biosensor capabilities and data interpretation.
• Further research is needed to address existing challenges and unlock future potential.