Paper
Knowledge Discovery from Observational Data of Causal Relationship between Clinical Procedures and Alzheimer’s Disease
- Authors:
- James Gomes; Suja Mani; Jean-Pierre Kapongo; Susie ElSaadany; Alya Danish; Soumaya Yacout
- Abstract
- In this paper, a knowledge discovery tool called Logical Analysis of Data is used to shed light on the causal relationship, if any, between three clinical procedures, namely blood transfusion, surgery and organ transplant, and Alzheimer’s disease, which is thought to be a prion-type disease of protein misfolding, capable of spreading infectiously from human to human. The Logical Analysis of Data is a data-mining artificial intelligence technique that allows the classification of phenomena based on knowledge extraction and pattern recognition, without the reliance on prior hypotheses or any statistical analysis.By creating a database of clinical information obtained from a systematic review of the literature on the risk factors of Alzheimer’s Disease, we were able to apply the Logical Analysis of Data to reveal the patterns distinguishing cases of AD that have undergone any of the three clinical procedures, and those cases that have not. Although several eye-opening patterns were revealed, results show that there is no evidence of relation between blood transfusion, surgery or organ transplant and the onset or development of Alzheimer’s disease.
- Keywords
- Data Mining; Logical Analysis of Data; Alzheimer’s Disease; Blood Transfusion; Surgery; Organ Transplant; Pattern Recognition; Systematic Review
- StartPage
- 1
- EndPage
- 10
- Doi
- 10.5963/PHF0201001