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        Significant prospects exist for enhancing healthcare in underprivileged regions through artificial intelligence (AI) and related technologies. AI applications that can raise health standards through cloud computing, mobile technology, and electronic medical record (EMR) systems will be very helpful to Africa. 

        The foundation for the deployment of cutting-edge AI technologies that can bridge the healthcare gap between developed and African nations has been established by these advancements. The broad definition of artificial intelligence in healthcare is information technology applied to computer behavior simulation. Usually, it refers to devices or computers that carry out operations meant to replicate the mental processes of humans in order to produce particular outcomes. Artificial intelligence technologies under treatment can be divided into multiple groups. Knowledge-based systems, sometimes referred to as expert systems, are programs created to use specialist knowledge to solve certain health issues. Algorithms are used in machine learning to find patterns in data and automatically learn from them. Neural networks are used in deep learning, a branch of machine learning, to handle unstructured input including text, audio, and images. With the use of natural language processing (NLP) technology, computers are now able to comprehend text authored by humans, recognize keywords, and examine patterns and relationships. Artificial intelligence planning, also known as automated planning and scheduling, sets priorities and arranges tasks to maximize productivity. Systems for processing images, sounds, and motions are known as image and signal processing systems.

        Early application of AI in healthcare in Africa began in Kenya in the middle of the 1980s. There, it was applied to enhance patient-provider communication and lead to a greater number of symptoms as described by the patient. Following that, Egypt developed an expert system in 1986 to enhance the identification of prevalent eye conditions. A variety of AI systems have recently been used throughout Africa to address health issues in underprivileged settings. For instance, by fusing epidemiological data with biophysical and meteorological data, the Council for Scientific and Industrial Research (CSIR) of South Africa has created an artificial intelligence system to forecast cholera epidemics.

        The adoption of cutting-edge artificial intelligence systems has been made easier by the broad availability of mobile technology in Africa, which has made cloud computing systems functional in even the most remote and resource-poor locations. One such is an artificial intelligence application in Nigeria that uses a smartphone app to identify a baby’s birth cry in order to anticipate birth asphyxia. In rural Africa, community health workers are vital.can profit from AI-programmed apps that enhance patient engagement and optimize their visits. In Zambia’s Copperbelt Province, a deep learning model utilizing convolutional neural networks aids in the diagnosis of diabetic retinopathy. Similar to this, Tanzania and Zambia have employed machine learning algorithms to identify tuberculosis from chest X-rays. 

        While many African languages have received little attention, new NLP models, such AfriBERTa15, are now concentrating on languages spoken by over 400 million people, including as Swahili, Afa, Oromo, and Amharic.Although AI technologies are particularly well-suited to handle the difficulties associated with rural and neglected healthcare, Africa is sometimes perceived as a technological laggard. This capacity has led to the adoption of numerous artificial intelligence initiatives across the continent. But only a small number of African nations Ethiopia, Ghana, Nigeria, South Africa, Kenya, and others have aggressively embraced AI in healthcare. Healthcare professionals are still not very familiar with AI technologies, even in these nations. To fully realize AI’s potential to revolutionize healthcare in Africa, essential infrastructure for safe data gathering, data security, governance, and training is needed. The vision of artificial intelligence driving healthcare in Africa may remain unfulfilled in the absence of these essential components.

References: https://www.iomcworld.org/open-access/application-of-artificial-intelligence-systems-to-improve-healthcare-delivery-in-africa-88986.html