Managerial Capstone: AI/ML in Developing Country Healthcare

This Managerial Capstone Project, submitted for a Global MBA at the University of Bedfordshire, presents a systematic review of the literature on the role of Artificial Intelligence (AI) and Machine Learning (ML) in improving clinical diagnosis and patient care in developing countries. The research, based on the PRISMA methodology, analyzes 50 documents and 100 articles. Findings indicate AI's potential to enhance medical research and data recording, and support early cancer detection. However, the study also highlights challenges such as limited resources and high costs associated with ML talent acquisition in these regions. The project concludes that while AI offers significant promise for healthcare advancements, further research is crucial to address the specific needs and limitations of developing countries, ultimately improving their healthcare conditions. The project also includes references to various research papers.

The Managerial Capstone Project
Role of Artificial intelligence and machine learning
in improving clinical diagnosis and patients care in
developing countries: a systematic review of the
literature
Submitted in partial fulfillement of the
requirements for the degree of the Global MBA
By Ahmed Ben Sassi
Student Reference : 1931293
University of Bedfordshire

4. Research findings
After conducting online research on effects of artificial intelligence and machine learning in developing
countries. 50 documents and 100 articles were reviewed online using PRISMA method of analyzing the
result research. The following were findings:
Artificial intelligence impact clinical diagnosis and patients care in developing countries
More than 80 articles were analyzed on how artificial intelligence can be used to improve
medical research and activities in the developing countries. During the research I managed to
gather data showing on how natural language processing through artificial intelligence can save
time of recording data by doctors in this nation (Jiang et al, 2014). Research also showed how
data from smart algorithm through screening of mammograph strategy in developing countries
healthcare can help through use of electronic medical report results, the cancers chances can be
analyzed and be shown by use of artificial intelligence results Lowr (2012).
Challenges in developing countries
The research found out that there were various challenges machine learning was facing in
developing countries. The lacking of machine learning resources was a major problem. Out of
100% recruiters, 65% of the recruiters in developing countries believe that no relevant skills are
sought after in a population according to online articles. The research also found out that the cost
for acquiring machine learning talent was so high such that annual pay is between $300,000 to
$500,000 which is very expensive for developing countries Scherer (2015).
5.Discussion
By adopting artificial intelligence developing countries have been posed by several challenges when
adopting artificial intelligence. This challenge is due to small economy that cannot support their artificial

intelligence growth (Johnson et al, 2018). But if adopted it can bring enormous change in health care
industry
Conclusion
The future of medical growth and improvement relies solely on artificial intelligence, hence need to do
more research regarding machine learning in developing countries in order to improve their health
conditions

Reference
Jiang, F., Jiang, Y., Zhi, H., Dong, Y., Li, H., Ma, S., ... & Wang, Y. (2017). Artificial intelligence in
healthcare: past, present and future. Stroke and vascular neurology, 2(4), 230-243.
Johnson, K. W., Soto, J. T., Glicksberg, B. S., Shameer, K., Miotto, R., Ali, M., ... & Dudley, J. T.
(2018). Artificial intelligence in cardiology. Journal of the American College of Cardiology,
71(23), 2668-2679.
Lohr, S. (2012). The age of big data. New York Times, 11(2012).
Scherer, M. U. (2015). Regulating artificial intelligence systems: Risks, challenges, competencies, and strategies.
Harv. JL & Tech., 29, 353.