Introduction
The Middle East is one of the fastest-growing regions in the world. With a population of more than 350 million, it has been identified as an emerging market with high potential. The region is also experiencing rapid economic growth and rising living standards. It’s no surprise that this region is expected to be home to some of the world’s most advanced healthcare systems shortly.
The way healthcare is delivered in the Middle East will change dramatically over the next few decades, largely due to advancements in Data Analytics and Artificial Intelligence (AI).
AI and big data analytics empower healthcare providers in the Middle East to make faster, more cost-effective diagnoses. However, Security worries concerning data privacy are growing in tandem with the increased usage of AI and big data.
This article examines how big data analytics and artificial intelligence (AI) are altering healthcare in this region and the implications for patients and healthcare professionals.
Making a Decision
Improving treatment necessitates the integration of big health data with fast and appropriate decisions. Clinical decision-making and actions can be aided by predictive analytics.
Pattern recognition is another area where AI is gaining traction in healthcare to determine who is at risk for developing a condition or whose condition may worsen due to lifestyle, environmental, genetic, or other factors.
Treatment
With Artificial Intelligence, clinicians can take a more holistic approach to disease management, better coordinate care plans, and help patients better manage and adhere to long-term treatment programs. They can also scan health records to identify people with chronic illnesses at risk.
Training
In a manner that simple computer-driven algorithms cannot, AI allows those in training to go through naturalistic simulations. Because of the emergence of natural speech and the ability of an AI machine to draw instantaneously from an extensive database of scenarios, a trainee’s answer to questions, decisions, or suggestions can be challenging in ways that a human cannot. Furthermore, the training program can learn from the trainee’s initial responses, allowing the challenges to be regularly changed to fit their learning needs.
Genomics
AI has the potential to alter our perceptions of genetics and push the boundaries of genomics study. According to new research, an artificial neural network can recognize and detect patterns in enormous volumes of genetic data, showing groupings and sequences of genes linked to specific diseases.
The complexity of genetic data has made progress in genomics difficult. Practitioners currently expect breakthroughs in genomic research thanks to AI’s ability to categorize and analyze a large amount of data quickly.
Conclusion
Even though life expectancy is higher than ever, there is a severe shortage of healthcare workers to meet the demand. There is also apprehension regarding expense management and control. Healthcare professionals should seek new technology to reduce costs and support human carers. Healthcare workers must take advantage of AI and Big Data technology to be ready for challenges.
