Expression of Concern for: A Comparative Exploration of Machine Learning Algorithms for Disease Detection
Alzheimer's disease (Promotion) is an unsolvable ongoing issue that causes cerebral disintegration, which results in memory loss and mental deterioration. Machine learning techniques are widely used in a variety of healthcare disciplines. A remarkable amount of research has gone into characteri...
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Published in | 2022 Fourth International Conference on Emerging Research in Electronics, Computer Science and Technology (ICERECT) p. 1 |
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Main Authors | , |
Format | Conference Proceeding |
Language | English |
Published |
IEEE
26.12.2022
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Online Access | Get full text |
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Summary: | Alzheimer's disease (Promotion) is an unsolvable ongoing issue that causes cerebral disintegration, which results in memory loss and mental deterioration. Machine learning techniques are widely used in a variety of healthcare disciplines. A remarkable amount of research has gone into characterizing Alzheimer's disease. In order to provide a better understanding of the work that has been completed in the subject of Alzheimer's disease, we have reviewed several articles by various experts that use various machine learning techniques collectively. One of the major problems in recent years has been Alzheimer's disease. Due to this illness, people lost their capacity for comprehension and reasoning, among other things. Applying machine learning research to attractive reverberation imaging (X-ray) techniques can help determine promotion more quickly and may help predict the progression of the disease. It was also possible to predict individual dementia in older adults using Promotion screening data and ML classifiers. The X-ray segment data and the patient's prior states can help in improving the classifier execution to predict the Promotion subject status. |
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DOI: | 10.1109/ICERECT56837.2022.10703586 |