2021
DOI: 10.1007/s11042-021-10506-x
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Visualizing correlations among Parkinson biomedical data through information retrieval and machine learning techniques

Abstract: In the last few years, the integration of researches in Computer Science and medical fields has made available to the scientific community an enormous amount of data, stored in databases. In this paper, we analyze the data available in the Parkinson’s Progression Markers Initiative (PPMI), a comprehensive observational, multi-center study designed to identify progression biomarkers important for better treatments for Parkinson’s disease. The data of PPMI participants are collected through a comprehensive batte… Show more

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Cited by 5 publications
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“…Biomedical data have been analyzed and visualized by Frasca & Tortora [5] to identify correlations between the medical reports of Parkinson's patients. To correlate the information of each patient's medical report, Information Retrieval and Machine Learning techniques have been adopted, including the Latent Semantic Analysis, Text2Vec, and Doc2Vec techniques.…”
mentioning
confidence: 99%
“…Biomedical data have been analyzed and visualized by Frasca & Tortora [5] to identify correlations between the medical reports of Parkinson's patients. To correlate the information of each patient's medical report, Information Retrieval and Machine Learning techniques have been adopted, including the Latent Semantic Analysis, Text2Vec, and Doc2Vec techniques.…”
mentioning
confidence: 99%