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Predictive informatics

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This is an old revision of this page, as edited by Stemonitis (talk | contribs) at 06:30, 19 July 2007 (moved Predictive Informatics to Predictive informatics: not a proper noun). The present address (URL) is a permanent link to this revision, which may differ significantly from the current revision.

Predictive informatics comprises the data, knowledge, and technology needed to conduct predictive analytics in industries such as healthcare, pharmaceuticals, life sciences and business. Predictive informatics enables researchers, analysts, physicians and decision-makers to aggregate and analyze disparate types of data, recognize patterns and trends within that data, and make more informed decisions that may preemptively alter future outcomes.

Elements of Predictive Informatics

Predictive informatics is a subset of informatics, thus incorporating the concepts and technology associated with information systems, data acquisition, data integration, data modeling, data mining, decision support systems, and data analysis.

Current Uses of Predictive Informatics

Healthcare

The demand for effective predictive informatics in healthcare has increased significantly as the demand for more quality and better outcomes has increased. Clinical researchers, healthcare administrators, and physicians seek to aggregate research and clinical data in order to improve long-range disease management strategies as well as make better real-time decisions.

Over the past decade the increased usage of electronic health records has produced vast amounts of clinical data that is now computable. Predictive informatics integrates this data with other datasets (e.g., genotypic, phenotypic) in centralized and standardized data repositories upon which predictive analytics may be conducted.

Pharmaceuticals

The biopharmaceutical industry uses predictive informatics (a superset of chemoinformatics) to integrate information resources to transform data into knowledge in order to make better decisions faster in the area of drug lead identification and optimization.

Systems Biology

Scientists involved in systems biology employ predictive informatics to integrate complex data about the interactions in biological systems from diverse experimental sources.

Other Uses

Predictive informatics and analytics are also used in financial services, insurance, telecommunications, retail, and travel industries.

See also

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