Registries for Evaluating Patient Outcomes

Registries for Evaluating Patient Outcomes

Author: Agency for Healthcare Research and Quality/AHRQ

Publisher: Government Printing Office

Published: 2014-04-01

Total Pages: 385

ISBN-13: 1587634333

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This User’s Guide is intended to support the design, implementation, analysis, interpretation, and quality evaluation of registries created to increase understanding of patient outcomes. For the purposes of this guide, a patient registry is an organized system that uses observational study methods to collect uniform data (clinical and other) to evaluate specified outcomes for a population defined by a particular disease, condition, or exposure, and that serves one or more predetermined scientific, clinical, or policy purposes. A registry database is a file (or files) derived from the registry. Although registries can serve many purposes, this guide focuses on registries created for one or more of the following purposes: to describe the natural history of disease, to determine clinical effectiveness or cost-effectiveness of health care products and services, to measure or monitor safety and harm, and/or to measure quality of care. Registries are classified according to how their populations are defined. For example, product registries include patients who have been exposed to biopharmaceutical products or medical devices. Health services registries consist of patients who have had a common procedure, clinical encounter, or hospitalization. Disease or condition registries are defined by patients having the same diagnosis, such as cystic fibrosis or heart failure. The User’s Guide was created by researchers affiliated with AHRQ’s Effective Health Care Program, particularly those who participated in AHRQ’s DEcIDE (Developing Evidence to Inform Decisions About Effectiveness) program. Chapters were subject to multiple internal and external independent reviews.


2016 Catalog of Federal Domestic Assistance

2016 Catalog of Federal Domestic Assistance

Author: United States. Congress. Senate. Office of Management and Budget. Executive Office of the President

Publisher:

Published: 2016

Total Pages: 1780

ISBN-13: 9780160936340

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Identifies and describes specific government assistance opportunities such as loans, grants, counseling, and procurement contracts available under many agencies and programs.


Enterprise Level Security 1 & 2

Enterprise Level Security 1 & 2

Author: Kevin Foltz

Publisher: CRC Press

Published: 2022-05-29

Total Pages: 752

ISBN-13: 1000165175

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This set comprises of Enterprise Level Security and Enterprise Level Security 2. ELS provides a modern alternative to the fortress approach to security. ELS 2 follows on from the first book, which covered the basic concepts of ELS, to give a discussion of advanced topics and solutions.


Data-Driven Approach for Bio-medical and Healthcare

Data-Driven Approach for Bio-medical and Healthcare

Author: Nilanjan Dey

Publisher: Springer Nature

Published: 2022-10-27

Total Pages: 238

ISBN-13: 9811951845

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The book presents current research advances, both academic and industrial, in machine learning, artificial intelligence, and data analytics for biomedical and healthcare applications. The book deals with key challenges associated with biomedical data analysis including higher dimensions, class imbalances, smaller database sizes, etc. It also highlights development of novel pattern recognition and machine learning methods specific to medical and genomic data, which is extremely necessary but highly challenging. The book will be useful for healthcare professionals who have access to interesting data sources but lack the expertise to use data mining effectively.


Appendix 3

Appendix 3

Author: United States. Army. Corps of Engineers

Publisher:

Published: 1966

Total Pages: 374

ISBN-13:

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MACHINE LEARNING FOR DATA SCIENCE - USING ML ALGORITHMS FOR PREDICTIVE MODELING

MACHINE LEARNING FOR DATA SCIENCE - USING ML ALGORITHMS FOR PREDICTIVE MODELING

Author: Dilip Siddareddy

Publisher: Xoffencerpublication

Published: 2023-10-30

Total Pages: 203

ISBN-13: 8119534603

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Because of the advancements that have been made in machine learning, the world is being changed in ways that are difficult to conceive. If you stop for a second and take a good look around, you'll see that the area of data science is everywhere you turn. Take, for example, Alexa from Amazon; she is an artificial intelligence that has been developed to be as simple and straightforward to use as is humanly conceivable. There are many other digital assistants similar to Alexa, such as Google Assistant, Cortana, and so on. Alexa is not the only one of its sort. Therefore, the question of why they were formed in the first place is the most crucial one to ask; the question of how they developed is the second most important one to ask. In any event, we are going to make an attempt to study each and every one of these issues, and we are also going to make an effort to devise answers that are both logical and technological in nature. Within the scope of this discussion, the question that has to be inquired about first and foremost is, "What exactly are Machine Learning and Data Science?" A widespread misconception is that data science and machine learning are interchangeable terms for the same thing. Those people do have a point, to some extent, considering that data science is nothing more than taking a huge amount of data and analyzing it using a variety of machine learning approaches, methodologies, and technologies. Therefore, in order to become an expert in data science, you need to have a solid understanding of mathematics and statistics, in addition to a profound comprehension of the area that you intend to specialize in. To be more specific, what does it mean to have "subject expertise"? Subject expertise is nothing more than the knowledge necessary about a given topic in order to be able to abstract and calculate the data that pertains to that field, as the name of this type of expertise indicates. In a nutshell, these three concepts are considered as the foundations of data science, and if you are successful in mastering all of them, then you should rejoice yourself because you have achieved the level of an A-level data scientist.


Anatomy of Orofacial Structures

Anatomy of Orofacial Structures

Author: Richard W Brand

Publisher: Elsevier Health Sciences

Published: 2017-12-08

Total Pages: 526

ISBN-13: 0323570089

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Anatomy of Orofacial Structures: A Comprehensive Approach, 8th Edition, gives you a clear understanding of oral histology and embryology, dental anatomy, and head and neck anatomy – all in a single resource. With new clinical content, a new chapter on the anatomy of local anesthesia, and an outstanding new full-color art program, this new edition is perfect for anyone studying to be a Dental Assistant or a Dental Hygienist. In addition, it offers the benefits of a combined text and student workbook, with review questions and unit tests, as well as detachable flashcards for on-the-go study – making this one product a complete learning package. - Comprehensive coverage of all areas of dental sciences includes oral histology and embryology, dental anatomy, and head and neck anatomy. - Updated, detailed anatomical illustrations support the material, including labeled line drawings, radiographs, and clinical photographs. - Text/Workbook format includes a perforated workbook section with chapter-by-chapter questions. - Removable flashcards feature an image of a tooth on one side and that tooth's identifying/important information on the other side, providing an easy and effective study tool. - NEW! Chapter on the anatomy of local anesthesia details application techniques. - NEW! Updated clinical content throughout focuses on evidence-based practice. - NEW! Full-color program features modern illustrations, histographs, micrographs, and clinical images. - NEW! Updated test bank with cognitive question leveling and mapping to Certified Dental Assistant (CDA) exam and National Board Dental Hygiene Examination (NBDHE) blueprints.