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Denormalization is a strategy used on a previously-normalized database to increase performance. In computing , denormalization is the process of trying to improve the read performance of a database , at the expense of losing some write performance, by adding redundant copies of data or by grouping data.
The Healthcare Cost and Utilization Project (HCUP, pronounced "H-Cup") is a family of healthcare databases and related software tools and products from the United States that is developed through a Federal-State-Industry partnership and sponsored by the Agency for Healthcare Research and Quality (AHRQ).
The Health Information Technology for Economic and Clinical Health Act portion of this stimulus law provides payments for providers that show they have reached the standard for “meaningful use”. [3] This has led more hospitals to adopt EMR, though they have had different experiences in adopting electronic medical records.
The patient health record is the primary legal record documenting the health care services provided to a person in any aspect of the health care system. The term includes routine clinical or office records, records of care in any health related setting, preventive care, lifestyle evaluation, research protocols and various clinical databases.
If a relational schema is in BCNF, then all redundancy based on functional dependency has been removed, [4] although other types of redundancy may still exist. A relational schema R is in Boyce–Codd normal form if and only if for every one of its functional dependencies X → Y, at least one of the following conditions hold: [5]
It was difficult to train, and required careful hyperparameter tuning and a "warm-up" in learning rate, where it starts small and gradually increases. The pre-LN convention, proposed several times in 2018, [ 28 ] was found to be easier to train, requiring no warm-up, leading to faster convergence.
A large part of industry focus of implementation of AI in the healthcare sector is in the clinical decision support systems. As more data is collected, machine learning algorithms adapt and allow for more robust responses and solutions. [111] Numerous companies are exploring the possibilities of the incorporation of big data in the healthcare ...
An entity–attribute–value model (EAV) is a data model optimized for the space-efficient storage of sparse—or ad-hoc—property or data values, intended for situations where runtime usage patterns are arbitrary, subject to user variation, or otherwise unforeseeable using a fixed design.