Researchers' from Pennsylvania State University (Penn State) Report Details of New Studies and Findings in the Area of Artificial Intelligence (420 Computable Phenotyping with "Big Data" as a Foundation for Artificial Intelligence Algorithm...
In: Diabetes Week, 2024-04-15, S. 318
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Researchers from Pennsylvania State University have conducted a study on the use of artificial intelligence (AI) and machine learning (ML) algorithms in the field of endocrinology. The study focused on the development of a disease-agnostic computable phenotype framework for ML algorithm construction, using male puberty as a case example. The researchers found that males diagnosed with precocious puberty were 6.89 times more likely to develop type II diabetes (T2D) between the ages of 14-18 compared to those without precocious puberty. The next steps involve training an AI/ML algorithm on the health data of different computable phenotype groups to identify underlying pathophysiologic variables. This research provides valuable insights into the potential use of AI and ML in understanding disease development. [Extracted from the article]
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Researchers' from Pennsylvania State University (Penn State) Report Details of New Studies and Findings in the Area of Artificial Intelligence (420 Computable Phenotyping with "Big Data" as a Foundation for Artificial Intelligence Algorithm...
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Zeitschrift: | Diabetes Week, 2024-04-15, S. 318 |
Veröffentlichung: | 2024 |
Medientyp: | serialPeriodical |
ISSN: | 1537-1425 (print) |
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