Publications by authors named "S Bersimis"

Computational Medicine encompasses the application of Statistical Machine Learning and Artificial Intelligence methods on several traditional medical approaches, including biochemical testing which is extremely valuable both for early disease prognosis and long-term individual monitoring, as it can provide important information about a person's health status. However, using Statistical Machine Learning and Artificial Intelligence algorithms to analyze biochemical test data from Electronic Health Records requires several preparatory steps, such as data manipulation and standardization. This study presents a novel approach for utilizing Electronic Health Records from large, real-world databases to develop predictive precision medicine models by exploiting Artificial Intelligence.

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Optimizing text preprocessing and text classification algorithms is an important, everyday task in large organizations and companies and it usually involves a labor-intensive and time-consuming effort. For example, the filtering and sorting of a large number of electronic mails (emails) are crucial to keeping track of the received information and converting it automatically into useful and profitable knowledge. Business emails are often unstructured, noisy, and with many abbreviations and acronyms, which makes their handling a challenging procedure.

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Identifying and locating areas - hot spots - that present high concentration of observations in a high-dimensional data set is crucial in many data processing and analysis methods and techniques, since observations that belong to the same hot spot share information and behave in a similar way. A useful tool towards that aim is the reduction of the data dimensionality and the graphical representation of them. In the present paper, a new method to identify and locate hot spots is proposed, based on the Andrews curves.

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Article Synopsis
  • Assessing agreement between raters is crucial in medical practice, but traditional techniques using contingency tables can delay results due to sample size requirements.
  • A new nonparametric sequential test is introduced that allows for immediate assessment of agreement as data is collected without needing a contingency table.
  • The proposed method shows strong performance with smaller sample size requirements and offers a unified approach to evaluating agreement among two or more raters and various characteristics.
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Telomerase is involved in the elongation of telomeres. It remains active in very few types of cell in mature organisms. One such cell type is the lymphocytes.

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