Medical Knowledge Extraction

Author : Constantinos M. Koutsojannis
Publisher : Unknown
Page : 247 pages
File Size : 43,9 Mb
Release : 2020
Category : Big data
ISBN : 1536179256

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Medical Knowledge Extraction from Big Data by Constantinos M. Koutsojannis Pdf

Data mining refers to the activity of going through big data sets to look for relevant information. As human health care data are the most difficult of all data to collect and their primary direction is the treatment of patients, and secondarily dealing with research, almost the only vindication for collecting medical data is to benefit the disease. All data miners should take into account that Medical Knowledge Extraction is internally connected with the Evidence-Based Medical approach because it uses data for already treated or not patients and there are times that opposites to Guideline Based medical practice. Additonally all researchers should be aware when are dealing with medical databases they may face the possibility that their work will never be accepted or even used from health care professionals if all these obligations will not be correctly addressed from the early beginning.In the present book, one can find after the three introductory chapters, a number of successfully evaluated applications that have been developed after mining approaches in Big or smaller amount (according to the application) of medical Data in different fields of every day clinical practice from teams of experts.The challenging adventure of Medical Knowledge Extraction can be followed by ambitious researchers finally resulting in a successful decision support system, that some times is so novel that it will provide new directions for basic or clinical research further that the existed. At least this procedure will save the experience of the best doctors on duty and will help young residents to be better and better.

Author : Alexander Scarlat
Publisher : Createspace Independent Publishing Platform
Page : 400 pages
File Size : 42,5 Mb
Release : 2018-03-19
Category : Electronic
ISBN : 1544093373

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Medical Information Extraction and Analysis by Alexander Scarlat Pdf

Book introduces clinicians to SQL and using hands on examples on MIMIC2 - a publicly available, de-identified ICU database from Beth Israel Deaconess Medical Center and MIT Physionet - it enables care providers to query any database of an Electronic Health Record (EHR) and create meaningful reports to support their quality initiatives. IT professionals will benefit from a structured analysis of the main parameters that interest clinicians: diagnosis, procedure, lab, meds, imaging reports, nursing assessments and interventions, scoring systems, mortality, length of stay, readmissions' rate, costs, etc. Using this book, both clinicians and IT professionals can easily retrieve any information from the data in their EHR and discover new clinical insights hidden in their database. 1. A Brief Database Primer 1 2. MIMIC2 Clinical Database 9 3. MySQL Workbench 12 4. Introduction to the Mighty SELECT 21 5. Aggregate / Summary Functions 48 6. Querying Multiple Tables 63 7. Entity Relationship Diagram - ERD 76 8. Systematic information extraction 91 9. Patient 102 10. Mortality 125 11. Length of stay (LOS) 139 12. Readmissions 145 13. Diagnosis 153 14. Sepsis profile 174 15. Lab 200 16. Drug 217 17. Procedure 230 18. Chart, note and much more 239 19. Provider and care unit 248 20. Nursing 259 21. Fluid 267 22. Score and scale 274 Appendix Answers to Questions

Author : Ankica Babić
Publisher : Unknown
Page : 97 pages
File Size : 48,5 Mb
Release : 1992
Category : Electronic
ISBN : 9178708710

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Medical Knowledge Extraction by Ankica Babić Pdf

Author : Tiwari, Vivek,Tiwari, Basant,Thakur, Ramjeevan Singh,Gupta, Shailendra
Publisher : IGI Global
Page : 358 pages
File Size : 47,5 Mb
Release : 2016-07-22
Category : Computers
ISBN : 9781522505372

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Pattern and Data Analysis in Healthcare Settings by Tiwari, Vivek,Tiwari, Basant,Thakur, Ramjeevan Singh,Gupta, Shailendra Pdf

Business and medical professionals rely on large data sets to identify trends or other knowledge that can be gleaned from the collection of it. New technologies concentrate on data’s management, but do not facilitate users’ extraction of meaningful outcomes. Pattern and Data Analysis in Healthcare Settings investigates the approaches to shift computing from analysis on-demand to knowledge on-demand. By providing innovative tactics to apply data and pattern analysis, these practices are optimized into pragmatic sources of knowledge for healthcare professionals. This publication is an exhaustive source for policy makers, developers, business professionals, healthcare providers, and graduate students concerned with data retrieval and analysis.

Author : Andreas Holzinger,Peter Kieseberg,A Min Tjoa,Edgar Weippl
Publisher : Springer Nature
Page : 552 pages
File Size : 51,5 Mb
Release : 2020-08-19
Category : Computers
ISBN : 9783030573218

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Machine Learning and Knowledge Extraction by Andreas Holzinger,Peter Kieseberg,A Min Tjoa,Edgar Weippl Pdf

This book constitutes the refereed proceedings of the 4th IFIP TC 5, TC 12, WG 8.4, WG 8.9, WG 12.9 International Cross-Domain Conference, CD-MAKE 2020, held in Dublin, Ireland, in August 2020. The 30 revised full papers presented were carefully reviewed and selected from 140 submissions. The cross-domain integration and appraisal of different fields provides an atmosphere to foster different perspectives and opinions; it will offer a platform for novel ideas and a fresh look on the methodologies to put these ideas into business for the benefit of humanity. Due to the Corona pandemic CD-MAKE 2020 was held as a virtual event.

Author : Ankica Babić
Publisher : Unknown
Page : 150 pages
File Size : 41,7 Mb
Release : 1993
Category : Electronic
ISBN : 9178711770

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Medical knowledge extraction by Ankica Babić Pdf

Author : Adam Bohr,Kaveh Memarzadeh
Publisher : Academic Press
Page : 385 pages
File Size : 40,7 Mb
Release : 2020-06-21
Category : Computers
ISBN : 9780128184394

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Artificial Intelligence in Healthcare by Adam Bohr,Kaveh Memarzadeh Pdf

Artificial Intelligence (AI) in Healthcare is more than a comprehensive introduction to artificial intelligence as a tool in the generation and analysis of healthcare data. The book is split into two sections where the first section describes the current healthcare challenges and the rise of AI in this arena. The ten following chapters are written by specialists in each area, covering the whole healthcare ecosystem. First, the AI applications in drug design and drug development are presented followed by its applications in the field of cancer diagnostics, treatment and medical imaging. Subsequently, the application of AI in medical devices and surgery are covered as well as remote patient monitoring. Finally, the book dives into the topics of security, privacy, information sharing, health insurances and legal aspects of AI in healthcare. Highlights different data techniques in healthcare data analysis, including machine learning and data mining Illustrates different applications and challenges across the design, implementation and management of intelligent systems and healthcare data networks Includes applications and case studies across all areas of AI in healthcare data

Author : Anonim
Publisher : Unknown
Page : 150 pages
File Size : 51,6 Mb
Release : 1993
Category : Electronic
ISBN : 917871592X

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Medical Knowledge Extraction by Anonim Pdf

Author : Amy Neustein
Publisher : Walter de Gruyter GmbH & Co KG
Page : 284 pages
File Size : 52,5 Mb
Release : 2014-10-09
Category : Computers
ISBN : 9781614513902

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Text Mining of Web-Based Medical Content by Amy Neustein Pdf

•Includes Text Mining and Natural Language Processing Methods for extracting information from electronic health records and biomedical literature. •Analyzes text analytic tools for new media such as online forums, social media posts, tweets and video sharing. •Demonstrates how to use speech and audio technologies for improving access to online content for the visually impaired. Text Mining of Web-Based Medical Content examines various approaches to deriving high quality information from online biomedical literature, electronic health records, query search terms, social media posts and tweets. Using some of the latest empirical methods of knowledge extraction, the authors show how online content, generated by both professionals and laypersons, can be mined for valuable information about disease processes, adverse drug reactions not captured during clinical trials, and tropical fever outbreaks. Additionally, the authors show how to perform infromation extraction on a hospital intranet, how to build a social media search engine to glean information about patients' own experiences interacting with healthcare professionals, and how to improve access to online health information. This volume provides a wealth of timely material for health informatic professionals and machine learning, data mining, and natural language researchers. Topics in this book include: •Mining Biomedical Literature and Clinical Narratives •Medication Information Extraction •Machine Learning Techniques for Mining Medical Search Queries •Detecting the Level of Personal Health Information Revealed in Social Media •Curating Layperson’s Personal Experiences with Health Care from Social Media and Twitter •Health Dialogue Systems for Improving Access to Online Content •Crowd-based Audio Clips to Improve Online Video Access for the Visually Impaired •Semantic-based Visual Information Retrieval for Mining Radiographic Image Data •Evaluating the Importance of Medical Terminology in YouTube Video Titles and Descriptions

Author : Andreas Holzinger,Peter Kieseberg,A Min Tjoa,Edgar Weippl
Publisher : Springer
Page : 379 pages
File Size : 45,8 Mb
Release : 2018-08-23
Category : Computers
ISBN : 9783319997407

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Machine Learning and Knowledge Extraction by Andreas Holzinger,Peter Kieseberg,A Min Tjoa,Edgar Weippl Pdf

This book constitutes the refereed proceedings of the IFIP TC 5, WG 8.4, 8.9, 12.9 International Cross-Domain Conference for Machine Learning and Knowledge Extraction, CD-MAKE 2018, held in Hamburg, Germany, in September 2018. The 25 revised full papers presented were carefully reviewed and selected from 45 submissions. The papers are clustered under the following topical sections: MAKE-Main Track, MAKE-Text, MAKE-Smart Factory, MAKE-Topology, and MAKE Explainable AI.

Author : Andreas Holzinger,Peter Kieseberg,A Min Tjoa,Edgar Weippl
Publisher : Unknown
Page : 0 pages
File Size : 41,7 Mb
Release : 2021
Category : Electronic
ISBN : 3030840611

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Machine Learning and Knowledge Extraction by Andreas Holzinger,Peter Kieseberg,A Min Tjoa,Edgar Weippl Pdf

This book constitutes the refereed proceedings of the 5th IFIP TC 5, TC 12, WG 8.4, WG 8.9, WG 12.9 International Cross-Domain Conference, CD-MAKE 2021, held in virtually in August 2021. The 20 full papers and 2 short papers presented were carefully reviewed and selected from 48 submissions. The cross-domain integration and appraisal of different fields provides an atmosphere to foster different perspectives and opinions; it will offer a platform for novel ideas and a fresh look on the methodologies to put these ideas into business for the benefit of humanity.

Author : Andreas Holzinger,Randy Goebel,Massimo Ferri,Vasile Palade
Publisher : Springer
Page : 207 pages
File Size : 53,7 Mb
Release : 2017-10-27
Category : Computers
ISBN : 9783319697758

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Towards Integrative Machine Learning and Knowledge Extraction by Andreas Holzinger,Randy Goebel,Massimo Ferri,Vasile Palade Pdf

The BIRS Workshop “Advances in Interactive Knowledge Discovery and Data Mining in Complex and Big Data Sets” (15w2181), held in July 2015 in Banff, Canada, was dedicated to stimulating a cross-domain integrative machine-learning approach and appraisal of “hot topics” toward tackling the grand challenge of reaching a level of useful and useable computational intelligence with a focus on real-world problems, such as in the health domain. This encompasses learning from prior data, extracting and discovering knowledge, generalizing the results, fighting the curse of dimensionality, and ultimately disentangling the underlying explanatory factors in complex data, i.e., to make sense of data within the context of the application domain. The workshop aimed to contribute advancements in promising novel areas such as at the intersection of machine learning and topological data analysis. History has shown that most often the overlapping areas at intersections of seemingly disparate fields are key for the stimulation of new insights and further advances. This is particularly true for the extremely broad field of machine learning.

Author : Andreas Holzinger,Peter Kieseberg,A Min Tjoa,Edgar Weippl
Publisher : Springer Nature
Page : 428 pages
File Size : 43,9 Mb
Release : 2019-08-22
Category : Computers
ISBN : 9783030297268

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Machine Learning and Knowledge Extraction by Andreas Holzinger,Peter Kieseberg,A Min Tjoa,Edgar Weippl Pdf

This book constitutes the refereed proceedings of the IFIP TC 5, TC 12, WG 8.4, 8.9, 12.9 International Cross-Domain Conference for Machine Learning and Knowledge Extraction, CD-MAKE 2019, held in Canterbury, UK, in August 2019. The 25 revised full papers presented were carefully reviewed and selected from 45 submissions. The cross-domain integration and appraisal of different fields provides an atmosphere to foster different perspectives and opinions; it will offer a platform for novel ideas and a fresh look on the methodologies to put these ideas into business for the benefit of humanity.

Author : Agency for Healthcare Research and Quality/AHRQ
Publisher : Government Printing Office
Page : 396 pages
File Size : 48,5 Mb
Release : 2014-04-01
Category : Medical
ISBN : 9781587634338

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Registries for Evaluating Patient Outcomes by Agency for Healthcare Research and Quality/AHRQ Pdf

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.

Author : Berka, Petr,Rauch, Jan,Zighed, Djamel Abdelkader
Publisher : IGI Global
Page : 464 pages
File Size : 53,5 Mb
Release : 2009-02-28
Category : Computers
ISBN : 9781605662190

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Data Mining and Medical Knowledge Management: Cases and Applications by Berka, Petr,Rauch, Jan,Zighed, Djamel Abdelkader Pdf

The healthcare industry produces a constant flow of data, creating a need for deep analysis of databases through data mining tools and techniques resulting in expanded medical research, diagnosis, and treatment. Data Mining and Medical Knowledge Management: Cases and Applications presents case studies on applications of various modern data mining methods in several important areas of medicine, covering classical data mining methods, elaborated approaches related to mining in electroencephalogram and electrocardiogram data, and methods related to mining in genetic data. A premier resource for those involved in data mining and medical knowledge management, this book tackles ethical issues related to cost-sensitive learning in medicine and produces theoretical contributions concerning general problems of data, information, knowledge, and ontologies.