{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,12]],"date-time":"2026-03-12T01:42:16Z","timestamp":1773279736860,"version":"3.50.1"},"reference-count":53,"publisher":"Oxford University Press (OUP)","issue":"2","content-domain":{"domain":["bmj.com"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2015,3,1]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>Objective To analyze the longitudinal data of multiple patients and to discover new temporal knowledge, we designed and developed the Visual Temporal Analysis Laboratory (ViTA-Lab). In this study, we demonstrate several of the capabilities of the ViTA-Lab framework through the exploration of renal-damage risk factors in patients with diabetes type II.<\/jats:p><jats:p>Materials and methods The ViTA-Lab framework combines data-driven temporal data mining techniques, with interactive, query-driven, visual analytical capabilities, to support, in an integrated fashion, an iterative investigation of time-oriented clinical data and of patterns discovered in them. Patterns discovered through the data mining mode can be explored visually, and vice versa. Both analysis modes are supported by a rich underlying ontology of clinical concepts, their relations, and their temporal properties. The knowledge enables us to apply a temporal-abstraction pre-processing phase that abstracts in a context-sensitive manner raw time-stamped data into interval-based clinically meaningful interpretations, increasing the results\u2019 significance. We demonstrate our approach through the exploration of risk factors associated with future renal damage (micro-albuminuria and macro-albuminuria) and their relationship to the hemoglobin A1C (HbA1C ) and creatinine level concepts, in the longitudinal records of 22\u2009000 patients with diabetes type II followed for up to 5\u2009years.<\/jats:p><jats:p>Results The iterative ViTA-Lab analysis process was highly feasible. Higher ranges of either normal albuminuria or normal creatinine values and their combination were shown to be significantly associated with future micro-albuminuria and macro-albuminuria. The risk increased given high HbA1C levels for women in the lower range of normal albuminuria, and for men in the higher range of albuminuria.<\/jats:p><jats:p>Conclusions The ViTA-Lab framework can potentially serve as a virtual laboratory for investigations of large masses of longitudinal clinical databases, for discovery of new knowledge through interactive exploration, clustering, classification, and prediction.<\/jats:p>","DOI":"10.1136\/amiajnl-2014-002927","type":"journal-article","created":{"date-parts":[[2014,10,29]],"date-time":"2014-10-29T03:49:40Z","timestamp":1414554580000},"page":"275-289","update-policy":"https:\/\/doi.org\/10.1136\/crossmarkpolicy","source":"Crossref","is-referenced-by-count":31,"title":["Exploration of patterns predicting renal damage in patients with diabetes type II using a visual temporal analysis laboratory"],"prefix":"10.1093","volume":"22","author":[{"given":"Denis","family":"Klimov","sequence":"first","affiliation":[{"name":"Department of 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