Abstract
Parkinson’s disease (PD) is a chronic disease. No treatment stops its progression, and it presents symptoms in multiple areas. One way to understand the PD population is to investigate the clustering of patients by demographic and clinical similarities. Previous PD cluster studies included scores from clinical surveys, which provide a numerical but ordinal, non-linear value. In addition, these studies did not include categorical variables, as the clustering method utilized was not applicable to categorical variables. It was discovered that the numerical values of patient age and disease duration were similar among past cluster results, pointing to the need to exclude these values. This paper proposes a novel and automatic discovery method to cluster PD patients by incorporating categorical variables. No estimate of the number of clusters is required as input, whereas the previous cluster methods require a guess from the end user in order for the method to be initiated. Using a patient dataset from the Parkinson’s Progression Markers Initiative (PPMI) website to demonstrate the new clustering technique, our results showed that this method provided an accurate separation of the patients. In addition, this method provides an explainable process and an easy way to interpret clusters and describe patient subtypes.
Highlights
Parkinson’s disease (PD) is a disabling and progressive disease, and it is prevalent in the ageing population [1]
PD diagnosis is based on clinical examination to determine whether any of the four motor symptoms are present: tremors at rest, rigidity, bradykinesia, and postural instability, with bradykinesia the most disabling feature that affects everything from fastening buttons to handwriting to the stopping of one or both arms swinging while walking, whereas tremors are involuntary movements caused by muscle contractions, which are the presenting feature in most cases [1]
A total of 47 clusters were discovered with the 6 categorical variables
Summary
Parkinson’s disease (PD) is a disabling and progressive disease, and it is prevalent in the ageing population [1]. The cause of the degeneration is unknown but it results in a loss of dopamine. Men may be 1.5 times more likely to be diagnosed with PD, with other possible risk factors including a family history of Parkinson’s disease, environmental factors, and even personality traits. People with a family history of the disease may have twice the risk [1]. PD diagnosis is based on clinical examination to determine whether any of the four motor symptoms are present: tremors at rest, rigidity, bradykinesia, and postural instability, with bradykinesia the most disabling feature that affects everything from fastening buttons to handwriting to the stopping of one or both arms swinging while walking, whereas tremors are involuntary movements caused by muscle contractions, which are the presenting feature in most cases [1]
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