The Performance Analysis of Health Care Automation using Artificial Intelligence Model

Artificial intelligence (AI) has shown great promise in healthcare, especially in healthcare automation. Without human input, AI systems are able to analyze vast volumes of data and make predictions and judgments based on that data. As a result, patient outcomes may be improved, and several healthcare systems may operate more accurately and efficiently. Processes in administration can be streamlined and optimized using AI. As a result, medical staff members are less burdened and can concentrate on giving patients high-quality treatment. AI's application in healthcare presents difficulties. A few issues to be concerned about are AI algorithms' lack of explainability and transparency, possible bias in the training data, and moral problems with patient privacy and data security. Medical diagnosis is a crucial area in which artificial intelligence has been used to automate healthcare. AI algorithms can produce diagnoses and treatment regimens by examining a patient's symptoms, medical history, and other pertinent information. This has demonstrated encouraging outcomes in raising the accuracy of diagnoses and lowering mistake rates.