Manara - Qatar Research Repository
10.1109_access.2023.3285596.pdf (2.98 MB)

Artificial Intelligence and Biosensors in Healthcare and Its Clinical Relevance: A Review

Download (2.98 MB)
journal contribution
submitted on 2024-02-14, 04:54 and posted on 2024-02-14, 04:54 authored by Rizwan Qureshi, Muhammad Irfan, Hazrat Ali, Arshad Khan, Aditya Shekhar Nittala, Shawkat Ali, Abbas Shah, Taimoor Muzaffar Gondal, Ferhat Sadak, Zubair Shah, Muhammad Usman Hadi, Sheheryar Khan, Qasem Al-Tashi, Jia Wu, Amine Bermak, Tanvir Alam

Data generated from sources such as wearable sensors, medical imaging, personal health records, and public health organizations have resulted in a massive information increase in the medical sciences over the last decade. Advances in computational hardware, such as cloud computing, graphical processing units (GPUs), Field-programmable gate arrays (FPGAs) and tensor processing units (TPUs), provide the means to utilize these data. Consequently, an array of sophisticated Artificial Intelligence (AI) techniques have been devised to extract valuable insights from the extensive datasets in the healthcare industry. Here, we present an overview of recent progress in AI and biosensors in medical and life sciences. We discuss the role of machine learning in medical imaging, precision medicine, and biosensors for the Internet of Things (IoT). We review the latest advancements in wearable biosensing technologies. These innovative solutions employ AI to assist in monitoring of bodily electro-physiological and electro-chemical signals, as well as in disease diagnosis. These advancements exemplify the trend towards personalized medicine, delivering highly effective, cost-efficient, and precise point-of-care treatment.Furthermore, an overview of the advances in computing technologies, such as accelerated AI, edge computing, and federated learning for medical data, are also documented. Finally, we investigate challenges in data-driven AI approaches, the potential issues generated by biosensors and IoT-based healthcare, and the distribution shifts that occur among different data modalities, concluding with an overview of future prospects.

Other Information

Published in: IEEE Access
See article on publisher's website:


Open Access funding provided by the Qatar National Library.



  • English



Publication Year

  • 2023

License statement

This Item is licensed under the Creative Commons Attribution 4.0 International License

Institution affiliated with

  • Hamad Bin Khalifa University
  • College of Science and Engineering - HBKU