Smart diagnostics devices through artificial intelligence and mechanobiological approaches

计算机科学 人工智能 检测点注意事项 智能设备 光容积图 生物医学工程 医学 人机交互 计算机视觉 病理 滤波器(信号处理)
作者
Dinesh Yadav,Ramesh Kumar Garg,Deepak Chhabra,Rajkumar Yadav,Ashwani Kumar,Pratyoosh Shukla
出处
期刊:3 biotech [Springer Science+Business Media]
卷期号:10 (8) 被引量:5
标识
DOI:10.1007/s13205-020-02342-x
摘要

The present work illustrates the promising intervention of smart diagnostics devices through artificial intelligence (AI) and mechanobiological approaches in health care practices. The artificial intelligence and mechanobiological approaches in diagnostics widen the scope for point of care techniques for the timely revealing of diseases by understanding the biomechanical properties of the tissue of interest. Smart diagnostic device senses the physical parameters due to change in mechanical, biological, and luidic properties of the cells and to control these changes, supply the necessary drugs immediately using AI techniques. The latest techniques like sweat diagnostics to measure the overall health, Photoplethysmography (PPG) for real-time monitoring of pulse waveform by capturing the reflected signal due to blood pulsation), Micro-electromechanical systems (MEMS) and Nano-electromechanical systems (NEMS) smart devices to detect disease at its early stage, lab-on-chip and organ-on-chip technologies, Ambulatory Circadian Monitoring device (ACM), a wrist-worn device for Parkinson’s disease have been discussed. The recent and futuristic smart diagnostics tool/techniques like emotion recognition by applying machine learning algorithms, atomic force microscopy that measures the fibrinogen and erythrocytes binding force, smartphone-based retinal image analyser system, image-based computational modeling for various neurological disorders, cardiovascular diseases, tuberculosis, predicting and preventing of Zika virus, optimal drugs and doses for HIV using AI, etc. have been reviewed. The objective of this review is to examine smart diagnostics devices based on artificial intelligence and mechanobiological approaches, with their medical applications in healthcare. This review determines that smart diagnostics devices have potential applications in healthcare, but more research work will be essential for prospective accomplishments of this technology.

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