To integrate disease prediction capabilities in healthcare using AI as it has significantly influenced the health sector through early diagnosis and focused treatment. A special focus of this work will be the discussion of the multitude of opportunities, and applications of AI in healthcare and disease prediction. To improve the accuracy of disease prediction at an early phase, we discuss the integration of new electronic health records applications with imaging and genomic databases. The advantages of using artificial intelligence are improving diagnostics, reducing costs in the healthcare sector, and developing individualized approaches. While incorporating artificial intelligence technologies in the healthcare sector is beneficial, incorporating enhanced artificial intelligence has drawbacks. The issues consist of privacy concerns, the lack of truly large, fully annotated datasets, the potential problem of bias present in AI algorithms, and the ability to easily integrate solutions into currently functional healthcare settings without leading to disruptions. Furthermore, the review also considers ethical and regulatory concerns of artificial intelligence in the healthcare sector. Moving toward the future, we briefly discuss how artificial intelligence can bring health care using predictive analysis techniques. In this Paper author describes the Opportunities and challenges of healthcare for various disease prediction and gives a summary of several machine learning models used to predict different diseases heart, kidney, diabetes, infertility, etc.