What is AI and Machine Learning?

AI is multiple technologies that can be combined in different ways to sense and comprehend. AI has the ability to learn from experience and it can adapt over time. It has the capacity to problem-solve and learn like a human brain. AI incorporates:  Natural Language Processing (“NLP”) and translation, pattern recognition, visual perception, and decision making. Machine Learning (ML), is the development of computational approaches to automatically make sense of data — this technology leverages that learning is a dynamic process. It is made possible through examples and experiences as opposed to pre-defined rules.

Like a human, a machine can retain information and becomes smarter over time. Unlike a human, a machine is not susceptible to sleep deprivation, distractions, information overload, and short-term memory loss — that is where this powerful technology becomes exciting.

 We are exploring new and innovated ways to help parents and their children control asthma. We are partnering with a national organization to distribute the Decoding Asthma series publications. Also we are in the early stages to incorporate an educational gamification version to accompany the books. The research has led us to the discussion and consideration of adding other components such as AI-based and Machine Learning tracking. We will also look at some existing examples on the market. 

 On the heels of ChatGPT headlines of 2023 AI has arrived! Recent global developments in AI are forcing us to think about its possibilities. Generative AI in healthcare has certainly been groundbreaking and it has reshaped and will continue the way we diagnose, treat, and monitor patients.

It can provide powerful tools to automate tasks and support and inform clinicians. Generative AI uses machine learning models to search medical data and uncover insights to help improve health outcomes and patient experiences.

Generative AI in it's different forms as related to digital healthcare will definitely be part of the conversation in new healthcare startups.