Harnessing the Power of Artificial Intelligence for Enhanced Point-of-Care Quality Control in Healthcare.

Improving Healthcare Quality Control: A Comprehensive Review on Harnessing Artificial Intelligence for Point-of-Care Enhancement


  • NGNOTOUOM NGNOKAM TANIA CYRIELLE Department of General Medicine, Université Evangélique en Afrique, Democratic Republic of Congo
  • ANGYIBA SERGE ANDIGEMA Department of Research and Education, Oli Health Magazine Organization, Kigali, Rwanda
  • MAFO KAMGA Lethicia Danaëlle Department of Microbiology, Immunology and Hematology; Faculty of medicine and Pharmaceutical Sciences, University of Dschang, Dschang, Cameroon
  • EWANE Ekwelle Department of Electronics and Electrical Engineering, College of Technology, University of Buea.




Artificial Intelligence, Quality control, Point-of-Care, Diagnosis, infectious diseases


Artificial intelligence (AI) is increasingly being used to improve the quality control of point-of-care diagnostics. This is caused by a number of factors, including the following: 1. AI can accelerate and improve testing accuracy. In comparison to humans, AI technology can review data more quickly and precisely, reducing errors and improving overall quality assurance. 2. When it comes to improving POC test findings on healthcare issues such as infectious diseases or medical crises such as heart attacks, AI can be used for sophisticated predictive analytics and modeling that aid in better decision-making. 3. Artificial intelligence facilitates process automation, increasing productivity and lowering labor costs in labor-intensive tasks such as testing and analyzing samples collected at point-of-care facilities. 4. The use of AI enables organizations implementing these solutions to gain insights from large volumes of raw diagnostic data generated faster and more accurately, allowing them to build solid frameworks around preventive care initiatives and significantly influence public health outcomes.5. Artificial intelligence (AI) has been demonstrated to be a useful tool for real-time monitoring systems that identify any problems with test results early so that they can be corrected before affected patients receive inaccurate diagnoses or treatment plans based on false information provided by diagnostic tests performed at points of care such as clinics or hospitals.

Using these technologies would allow healthcare organizations to spend less on labor while still receiving exact diagnoses and rapid treatment delivery at a fraction of the cost that manual approaches required earlier.


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How to Cite

TANIA CYRIELLE, N. N., SERGE ANDIGEMA, A., Lethicia Danaëlle, M. K., & Ekwelle, E. (2024). Harnessing the Power of Artificial Intelligence for Enhanced Point-of-Care Quality Control in Healthcare.: Improving Healthcare Quality Control: A Comprehensive Review on Harnessing Artificial Intelligence for Point-of-Care Enhancement. Asian Journal Of Medical Technology, 4(1), 22–33. https://doi.org/10.32896/ajmedtech.v4n1.22-33