Machine learning and Artificial intelligence are addressing some of the biggest challenges in healthcare, including real-time clinical decision support, precision medicine, population health management, and even curing cancer.

There may be a compelling role for machine learning in personally engaging with patients to improve the management of chronic health conditions such as diabetes, metabolic syndrome, etc. For successfully managing these conditions patients need to consistently manage their daily medical activities. To make this more effective, care management should be personalized to each patient’s lifestyle, preferences, needs, and medical specifics.

Machine learning turned out to be a potential solution in providing personalized care management based on the different data sources collected from wearable sensors, personal biometric devices, and smartphones, coupled with other types of information such as patient history and clinical guidelines to dynamically generate insights and provide personal recommendations to the patients and care providers.

Machine learning also helps in building new generation of apps which is easy-to-use and can reduce the burden of care providers and empower the patients with real-time personalized guidance in day-to-day life. To conclude, machine learning automates self-care and facilitates healthy behaviors rather than personally visiting the healthcare providers. With the power of machine learning the growing amount of health data is organized and continuously curated which in turn result in real time decision making.