Titlebook: Computational Intelligence in Healthcare Informatics; D. P. Acharjya,Kun Ma Book 2024 The Editor(s) (if applicable) and The Author(s), und

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https://doi.org/10.1007/978-3-322-86278-5 are required for storing and analysing it. The health industry has seen significant changes in recent years, with a growth in the number of physicians, patients, diseases, and technology. Doctors can analyse patient symptoms using data and information technology. Data mining is widely used for anal

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Vom Goldstandard zu Bretton-Woodstributing factors; hence earlier disease prediction is necessary for the conditions mentioned above. Osteoporosis and osteopenia generally affect older adults and women who have passed menopause to a greater extent. Early identification of osteoporosis and osteopenia is crucial to prevent bone fract

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Hedging der zukünftigen Zahlungsströmeearly detection and medication. The main cause of the disease is due to several genetic mutations which form cancer tumors. Identification of genetic mutation is a time-consuming task. This creates a lot of difficulties for the molecular pathologist. A molecular pathologist selects a list of gene va

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Strategien an den Devisenmärktenmputational techniques are used to improve the accuracy of disease diagnosis and reduce the diagnosis time, and the mortality rate. Advanced learning methods need to be used to improve efficacy and clinical significance. Machine learning methods are widely used in healthcare systems for screening, r

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https://doi.org/10.1007/978-3-322-91166-7ivate. There have been several efforts for analyzing and predicting future COVID-19 cases based on primary data. The present study is based on an inferential methodology which is one of the most widely used data science techniques in the study of events like COVID-19 time-series analysis. Analyzing

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https://doi.org/10.1007/978-981-99-8853-2Healthcare Informatics; Machine Learning in Healthcare; Computational Intelligence; Bio-inspired Algori