ABSTRACT.
Medical
Artificial Intelligence has established itself as a robust and fruitful field in the last 30 years. Most resource poor
countries face the triple burden of malaria, tuberculosis and HIV. This coupled
with the problems of lack of infrastructure, scarcity of clinical staff, and
complex clinical guide-lines, have encouraged the application of Artificial
Intelligence in healthcare management specifically on practical issues of field medical data collection, mining, and
better integration with healthcare workflow. although
the primary roles of AI in patient care to
date have mainly been in patient diagnosis and
image analysis, the future holds great potential for applying AI to improve
many aspects of the patient care process.
Some
example include personalizing treatments to maximize efficacy while minimizing
side effects, recommending
appropriate
sequences of diagnostic tests, monitoring the patient population’s health and
safety, and discovering new medical knowledge that can directly impact the
quality of care. Great challenges remain due to the health data’s size and
complexity, but the AI community is well on its way to meeting these challenges
by developing new pattern detection
techniques,
scalable algorithms, and novel approaches that use massive quantities of health
data to answer general questions.
One such
application is an HIV/AIDS antiretroviral therapy management system that uses
Artificial Intelligence algorithm to pre-dict drug resistance and the
progression of the disease. Another serious problem is the scarcity of personnel
with sufficient Artificial Intelligence knowledge in the medical field. A
distance education has shown its potential to remedy the problem.
INTRODUCTION
The healthcare system
faces many challenges, including skyrocketing costs, high rates of
drug-resistant and hospital-acquired infections, and failures of care delivery
leading to preventable adverse health events. Overtreatment, poor execution of
care, and failure to adopt best practices for preventive care and patient
safety have huge and directly measurable impacts on both healthcare costs and
patient outcomes.1,2 On the other hand, both the increasing availability of electronic
health data and the. . .
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