What Is AI in Healthcare?
AI in healthcare is an umbrella term to describe the application of machine learning (ML) algorithms and other cognitive technologies in medical settings. In the simplest sense, AI is when computers and other machines mimic human cognition, and are capable of learning, thinking, and making decisions or taking actions. AI in healthcare, then, is the use of machines to analyze and act on medical data, usually with the goal of predicting a particular outcome.
A significant AI use case in healthcare is the use of ML and other cognitive disciplines for medical diagnosis purposes. Using patient data and other information, AI can help doctors and medical providers deliver more accurate diagnoses and treatment plans. Also, AI can help make healthcare more predictive and proactive by analyzing big data to develop improved preventive care recommendations for patients.
Why Does AI in Healthcare Matter?
Healthcare is one of the most critical sectors in the broader landscape of big data because of its fundamental role in a productive, thriving society. The application of AI to healthcare data can literally be a matter of life and death. AI can assist doctors, nurses, and other healthcare workers in their daily work. AI in healthcare can enhance preventive care and quality of life, produce more accurate diagnoses and treatment plans, and lead to better patient outcomes overall. AI can also predict and track the spread of infectious diseases by analyzing data from a government, healthcare, and other sources. As a result, AI can play a crucial role in global public health as a tool for combatting epidemics and pandemics.