Outline the opportunities that Machine Learning presents for healthcare improvement. Provide a brief description of two common applications of Machine Learning in this context.

Machine Learning (ML) presents numerous opportunities for healthcare improvement. Here are some of them:

1. Predictive Analytics: ML can be used to predict patient outcomes based on their health data. This can help doctors make more informed decisions about treatment plans.

2. Personalized Medicine: ML can help in creating personalized treatment plans for patients based on their unique genetic makeup and health history.

3. Early Disease Detection: ML algorithms can analyze large amounts of data to detect patterns that may indicate the early stages of a disease.

4. Drug Discovery: ML can speed up the process of drug discovery by analyzing large amounts of data to identify potential drug candidates.

5. Hospital Management: ML can help in managing hospital resources more efficiently, such as predicting patient admission rates to better manage staff and resources.

Two common applications of Machine Learning in healthcare are:

1. Predictive Analytics: One of the most common applications of ML in healthcare is predictive analytics. For example, ML algorithms can analyze a patient's health data and predict the likelihood of them developing a certain disease. This can help doctors intervene early and potentially prevent the disease from developing.

2. Drug Discovery: ML is also commonly used in drug discovery. It can analyze large amounts of data to identify potential drug candidates. This can significantly speed up the process of drug discovery and make it more efficient.