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Published on: August 8, 2019

Smart diagnostics devices through artificial intelligence and mechanobiological approaches.

Dinesh Yadav¹, Ramesh Kumar Garg¹, Deepak Chhabra²

¹Department of Mechanical Engineering, Deenbandhu Chhotu Ram University of Science and Technology, Murthal, Haryana India.

|July 31, 2020

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Smart diagnostic devices leverage artificial intelligence (AI) and mechanobiology for early disease detection and personalized treatment. These AI-driven tools offer advanced point-of-care solutions for improved healthcare outcomes.

Area of Science:

Biomedical Engineering
Artificial Intelligence in Healthcare
Mechanobiology

Background:

Healthcare diagnostics are evolving with smart devices integrating AI and mechanobiology.
Understanding tissue biomechanics enables early disease detection at the point of care.
Smart devices can sense cellular changes and administer targeted therapies.

Purpose of the Study:

To review smart diagnostic devices utilizing AI and mechanobiological principles.
To explore their applications in modern healthcare practices.
To assess the potential and future directions of these technologies.

Main Methods:

Review of current and emerging smart diagnostic technologies.
Discussion of AI and machine learning algorithms in diagnostics.

Keywords:

Artificial intelligence Biological Diagnostics Fluidic Mechanical Mechanobiology

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Analysis of mechanobiological approaches for disease detection.

Main Results:

Technologies discussed include sweat diagnostics, Photoplethysmography (PPG), MEMS/NEMS devices, lab-on-chip, organ-on-chip, and Ambulatory Circadian Monitoring (ACM).
Future applications include emotion recognition, atomic force microscopy for binding forces, smartphone-based retinal analysis, and AI for disease prediction and drug optimization.
Smart devices show significant potential for early disease detection and personalized medicine.

Conclusions:

Smart diagnostic devices offer promising advancements in healthcare.
AI and mechanobiology are key drivers for innovative diagnostic tools.
Further research is crucial for realizing the full potential of smart diagnostics.