The strongest associations of medical diagnosis across the three cohorts.

a) HA-AKI, b) CA-AKI, and c) No-AKI. The diagnosis clusters identified by the community detection algorithms and designated as three colors: green, purple, and blue. Each Node (e.g., Z82.49, Z79.891 etc.) represent diagnosis, node siz...

وصف كامل

محفوظ في:

التفاصيل البيبلوغرافية
المؤلف الرئيسي:	Mohammad A. Al-Mamun (6086642) (author)
مؤلفون آخرون:	Ki Jin Jeun (17374655) (author), Todd Brothers (9383541) (author), Ernest O. Asare (12372721) (author), Khaled Shawwa (2586589) (author), Imtiaz Ahmed (574504) (author)
منشور في:	2025
الموضوعات:	Medicine Microbiology Cell Biology Developmental Biology Marine Biology Cancer Mathematical Sciences not elsewhere classified patient profiling algorithm ischemic heart disease including high cholesterol identify patient profiles identify clinical phenotypes gi tract components variable clustering methods top three clusters presented using comorbidities hospital acquired aki 876 ckd patients 37 ), osteoarthritis two methods three groups average comorbidities aki patients aki ), 14 ), xlink "> urgent need several conditions promising approach onset ckd mean number lactic acidosis higher number higher degree find similarities edges connected comorbidity network combining network classified aki ckd ). betweenness centrality based community aki groups aki group aki cohort 84 vs
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الوصف
الملخص:	<p><b>a)</b> HA-AKI, <b>b)</b> CA-AKI, and <b>c)</b> No-AKI. The diagnosis clusters identified by the community detection algorithms and designated as three colors: green, purple, and blue. Each Node (e.g., Z82.49, Z79.891 etc.) represent diagnosis, node size indicates prevalence, while edge thickness (i.e., line between two nodes) represents the observed‐to‐expected ratio (OER) (> 90<sup>th</sup> percentile).</p>

The strongest associations of medical diagnosis across the three cohorts.

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