White Paper

Small Data and AI for Healthcare

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Get an overview of Artificial Intelligence applied to medical research and healthcare and explore the possibilities offered through this technology.

AI and Machine Learning can be used in various ways to improve healthcare researches. It can be used in order to improve the organization and management of health structure but also to optimize the medical research. However, Small Data are truly efficient in order to enhance the day-to-day operational healthcare, i.e., caring for patients.

How can AI and Small Data helps healthcare practitioners?

Artificial Intelligence applied to small quantities of data (Small Data) can provide value for healthcare practitioners and medical researchers. The point here is to understand whether the specific data a hospital or a practitioner gathers in its practice is sufficient to build models that will help doctors. Those models can be used to predict and detect various forms of diseases. It could be used to predict COVID infection in patients, predict ICU admissions or even to diagnose uterus cancer based on genes.

Medical researchers and doctors can use Machine Learning on a medical database with reasonable accuracy. It can be used on a day-to-day basis by medical doctors to diagnose, understand. And it can be used daily by researchers, data analysts and scientists to explore and analyze. The models are fast to build, quick to run, and agile to apply to new patients’ cases. Nevertheless, it can do more than give predictions. It can contribute to enter into the data set’s heart and extract the critical criteria impacting the results. 

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