IBM trains AI to predict progression of Parkinson’s disease symptoms

Researchers from IBM and the Michael J. Fox Foundation (MJFF) developed an algorithm that predicts the progression of symptoms in a patient with Parkinson’s disease in terms of time and severity. The report was published in The Lancet Digital Health.

The researchers claim that the software will allow doctors to better forecast disease progression so that they can help patients cope with their symptoms.

“Our goal is to use artificial intelligence to assist in patient management and in the development of clinical research. This is important, because despite the prevalence of Parkinson’s disease, patients experience a unique variety of motor and non-motor symptoms,” IBM said.

According to the researchers, the creation of the algorithm was made possible thanks to a MJFF-sponsored initiative on markers of progression of Parkinson’s disease. This helped gather information on more than 1,400 people and consolidate it into a training dataset.

IBM described the dataset as “the largest and most reliable volume of longitudinal data on Parkinson’s patients to date.” It allowed the AI model to map complex patterns of symptoms and progression, they added.

IBM Research and MJFF plan to continue work on the AI algorithm. In the future they hope to improve it by providing more granular characteristics of the various stages of the disease.

Researchers estimate that more than 6 million people worldwide suffer from Parkinson’s disease. There is currently no cure.

In July, DeepMind’s AI lab researchers compiled the most comprehensive database of human protein structures, created by the AlphaFold neural network.

In June, IBM announced plans to build a centre for quantum computing and artificial intelligence in the United Kingdom with government support.

In March, scientists from NVIDIA and Harvard University developed an AI model that accelerates the analysis of the human genome.

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