The IBM researchers worked with Michael J. Fox Foundation to use AI to help predict the progress of Parkinson’s disease. Michael J. Fox is an American actor who is in a number of iconic films and TV series in the 80s. The actor has Parkinson’s disease for years, and his foundation works to help find drugs for this disease.

New research was recently published by a group that focused on a new artificial intelligence model that classified the pattern of typical symptoms of Parkinson’s disease. The model can predict the development of the disease by finding the time and severity of symptoms known. The model predicts time and severity by learning from longitudinal patient data.

The details of the new AI model are published in “Lancet Digital Health,” with researchers who record the model can predict the time and severity of the disease by utilizing longitudinal patient data, which is a description of clinical status of patients collected from time to time. The researchers said their goal was to use AI to help patient management and clinical trial design.

Parkinson’s is a fairly common disease that has an impact of 6 million globally. Regardless of how famous conditions and how wide throughout the world, people who fight this disease experience various motor and non-motor symptoms. The aim of the new AI is to use machine learning to learn from a large number of patient data and provide better doctors and researchers to predict the development of symptoms in each patient.

The researchers recorded patient data used by AI had been identified, and it was one of the largest Parkinson’s datasets in the world. Having access to massive data sets is very important for success in the machine learning model. The past study focuses on the characterization of Parkinson’s disease using basic information. However, this new method depends on patient data for up to seven years. Despite a variety of disease development paths, the AI ​​model can make accurate predictions.