Medical Information Extraction And Analysis

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Medical Information Extraction and Analysis

Alexander Scarlat
Medical Information Extraction and Analysis Book PDF

Author : Alexander Scarlat
Publisher : Createspace Independent Publishing Platform
Page : 400 pages
File Size : 47,9 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

Clinical Text Mining

Hercules Dalianis
Clinical Text Mining Book PDF

Author : Hercules Dalianis
Publisher : Springer
Page : 192 pages
File Size : 40,8 Mb
Release : 2018-05-14
Category : Computers
ISBN : 9783319785035

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Clinical Text Mining by Hercules Dalianis Pdf

This open access book describes the results of natural language processing and machine learning methods applied to clinical text from electronic patient records. It is divided into twelve chapters. Chapters 1-4 discuss the history and background of the original paper-based patient records, their purpose, and how they are written and structured. These initial chapters do not require any technical or medical background knowledge. The remaining eight chapters are more technical in nature and describe various medical classifications and terminologies such as ICD diagnosis codes, SNOMED CT, MeSH, UMLS, and ATC. Chapters 5-10 cover basic tools for natural language processing and information retrieval, and how to apply them to clinical text. The difference between rule-based and machine learning-based methods, as well as between supervised and unsupervised machine learning methods, are also explained. Next, ethical concerns regarding the use of sensitive patient records for research purposes are discussed, including methods for de-identifying electronic patient records and safely storing patient records. The book’s closing chapters present a number of applications in clinical text mining and summarise the lessons learned from the previous chapters. The book provides a comprehensive overview of technical issues arising in clinical text mining, and offers a valuable guide for advanced students in health informatics, computational linguistics, and information retrieval, and for researchers entering these fields.

Sentiment Analysis in the Medical Domain

Kerstin Denecke
Sentiment Analysis in the Medical Domain Book PDF

Author : Kerstin Denecke
Publisher : Springer Nature
Page : 151 pages
File Size : 51,8 Mb
Release : 2023-05-24
Category : Medical
ISBN : 9783031301872

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Sentiment Analysis in the Medical Domain by Kerstin Denecke Pdf

Sentiment analysis deals with extracting information about opinions, sentiments, and even emotions conveyed by writers towards topics of interest. Medical sentiment analysis refers to the identification and analysis of sentiments or emotions expressed in free-textual documents with a scope on healthcare and medicine. This fascinating problem offers numerous application areas in the domain of medicine, but also research challenges. The book provides a comprehensive introduction to the topic. The primary purpose is to provide the necessary background on medical sentiment analysis, ranging from a description of the notions of medical sentiment to use cases that have been considered already and application areas of relevance. Medical sentiment analysis uses natural language processing (NLP), text analysis and machine learning to realise the process of extracting and classifying statements regarding expressed opinion and sentiment. The book offers a comprehensive overview on existing methods of sentiment analysis applied to healthcare resources or health-related documents. It concludes with open research avenues providing researchers indications which topics still have to be developed in more depth.

Statistics and Machine Learning Methods for EHR Data

Hulin Wu,Jose Miguel Yamal,Ashraf Yaseen,Vahed Maroufy
Statistics and Machine Learning Methods for EHR Data Book PDF

Author : Hulin Wu,Jose Miguel Yamal,Ashraf Yaseen,Vahed Maroufy
Publisher : CRC Press
Page : 329 pages
File Size : 43,7 Mb
Release : 2020-12-09
Category : Business & Economics
ISBN : 9781000260946

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Statistics and Machine Learning Methods for EHR Data by Hulin Wu,Jose Miguel Yamal,Ashraf Yaseen,Vahed Maroufy Pdf

The use of Electronic Health Records (EHR)/Electronic Medical Records (EMR) data is becoming more prevalent for research. However, analysis of this type of data has many unique complications due to how they are collected, processed and types of questions that can be answered. This book covers many important topics related to using EHR/EMR data for research including data extraction, cleaning, processing, analysis, inference, and predictions based on many years of practical experience of the authors. The book carefully evaluates and compares the standard statistical models and approaches with those of machine learning and deep learning methods and reports the unbiased comparison results for these methods in predicting clinical outcomes based on the EHR data. Key Features: Written based on hands-on experience of contributors from multidisciplinary EHR research projects, which include methods and approaches from statistics, computing, informatics, data science and clinical/epidemiological domains. Documents the detailed experience on EHR data extraction, cleaning and preparation Provides a broad view of statistical approaches and machine learning prediction models to deal with the challenges and limitations of EHR data. Considers the complete cycle of EHR data analysis. The use of EHR/EMR analysis requires close collaborations between statisticians, informaticians, data scientists and clinical/epidemiological investigators. This book reflects that multidisciplinary perspective.

Medical Data Analysis and Processing using Explainable Artificial Intelligence

Om Prakash Jena,Mrutyunjaya Panda,Utku Kose
Medical Data Analysis and Processing using Explainable Artificial Intelligence Book PDF

Author : Om Prakash Jena,Mrutyunjaya Panda,Utku Kose
Publisher : CRC Press
Page : 269 pages
File Size : 52,7 Mb
Release : 2023-11-06
Category : Technology & Engineering
ISBN : 9781000983609

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Medical Data Analysis and Processing using Explainable Artificial Intelligence by Om Prakash Jena,Mrutyunjaya Panda,Utku Kose Pdf

The text presents concepts of explainable artificial intelligence (XAI) in solving real world biomedical and healthcare problems. It will serve as an ideal reference text for graduate students and academic researchers in diverse fields of engineering including electrical, electronics and communication, computer, and biomedical Presents explainable artificial intelligence (XAI) based machine analytics and deep learning in medical science Discusses explainable artificial intelligence (XA)I with the Internet of Medical Things (IoMT) for healthcare applications Covers algorithms, tools, and frameworks for explainable artificial intelligence on medical data Explores the concepts of natural language processing and explainable artificial intelligence (XAI) on medical data processing Discusses machine learning and deep learning scalability models in healthcare systems This text focuses on data driven analysis and processing of advanced methods and techniques with the help of explainable artificial intelligence (XAI) algorithms. It covers machine learning, Internet of Things (IoT), and deep learning algorithms based on XAI techniques for medical data analysis and processing. The text will present different dimensions of XAI based computational intelligence applications. It will serve as an ideal reference text for graduate students and academic researchers in the fields of electrical engineering, electronics and communication engineering, computer engineering, and biomedical engineering.

Registries for Evaluating Patient Outcomes

Agency for Healthcare Research and Quality/AHRQ
Registries for Evaluating Patient Outcomes Book PDF

Author : Agency for Healthcare Research and Quality/AHRQ
Publisher : Government Printing Office
Page : 396 pages
File Size : 44,5 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.

Text Mining of Web-Based Medical Content

Amy Neustein
Text Mining of Web Based Medical Content Book PDF

Author : Amy Neustein
Publisher : Walter de Gruyter GmbH & Co KG
Page : 286 pages
File Size : 49,6 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

Advanced Classification Techniques for Healthcare Analysis

Chakraborty, Chinmay
Advanced Classification Techniques for Healthcare Analysis Book PDF

Author : Chakraborty, Chinmay
Publisher : IGI Global
Page : 424 pages
File Size : 40,5 Mb
Release : 2019-02-22
Category : Medical
ISBN : 9781522577973

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Advanced Classification Techniques for Healthcare Analysis by Chakraborty, Chinmay Pdf

Medical and information communication technology professionals are working to develop robust classification techniques, especially in healthcare data/image analysis, to ensure quick diagnoses and treatments to patients. Without fast and immediate access to healthcare databases and information, medical professionals’ success rates and treatment options become limited and fall to disastrous levels. Advanced Classification Techniques for Healthcare Analysis provides emerging insight into classification techniques in delivering quality, accurate, and affordable healthcare, while also discussing the impact health data has on medical treatments. Featuring coverage on a broad range of topics such as early diagnosis, brain-computer interface, metaheuristic algorithms, clustering techniques, learning schemes, and mobile telemedicine, this book is ideal for medical professionals, healthcare administrators, engineers, researchers, academicians, and technology developers seeking current research on furthering information and communication technology that improves patient care.

Biomedical Data Mining for Information Retrieval

Sujata Dash,Subhendu Kumar Pani,S. Balamurugan,Ajith Abraham
Biomedical Data Mining for Information Retrieval Book PDF

Author : Sujata Dash,Subhendu Kumar Pani,S. Balamurugan,Ajith Abraham
Publisher : John Wiley & Sons
Page : 450 pages
File Size : 54,5 Mb
Release : 2021-08-24
Category : Computers
ISBN : 9781119711247

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Biomedical Data Mining for Information Retrieval by Sujata Dash,Subhendu Kumar Pani,S. Balamurugan,Ajith Abraham Pdf

BIOMEDICAL DATA MINING FOR INFORMATION RETRIEVAL This book not only emphasizes traditional computational techniques, but discusses data mining, biomedical image processing, information retrieval with broad coverage of basic scientific applications. Biomedical Data Mining for Information Retrieval comprehensively covers the topic of mining biomedical text, images and visual features towards information retrieval. Biomedical and health informatics is an emerging field of research at the intersection of information science, computer science, and healthcare and brings tremendous opportunities and challenges due to easily available and abundant biomedical data for further analysis. The aim of healthcare informatics is to ensure the high-quality, efficient healthcare, better treatment and quality of life by analyzing biomedical and healthcare data including patient’s data, electronic health records (EHRs) and lifestyle. Previously, it was a common requirement to have a domain expert to develop a model for biomedical or healthcare; however, recent advancements in representation learning algorithms allows us to automatically to develop the model. Biomedical image mining, a novel research area, due to the vast amount of available biomedical images, increasingly generates and stores digitally. These images are mainly in the form of computed tomography (CT), X-ray, nuclear medicine imaging (PET, SPECT), magnetic resonance imaging (MRI) and ultrasound. Patients’ biomedical images can be digitized using data mining techniques and may help in answering several important and critical questions relating to healthcare. Image mining in medicine can help to uncover new relationships between data and reveal new useful information that can be helpful for doctors in treating their patients. Audience Researchers in various fields including computer science, medical informatics, healthcare IOT, artificial intelligence, machine learning, image processing, clinical big data analytics.

Secondary Analysis of Electronic Health Records

MIT Critical Data
Secondary Analysis of Electronic Health Records Book PDF

Author : MIT Critical Data
Publisher : Springer
Page : 427 pages
File Size : 42,6 Mb
Release : 2016-09-09
Category : Medical
ISBN : 9783319437422

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Secondary Analysis of Electronic Health Records by MIT Critical Data Pdf

This book trains the next generation of scientists representing different disciplines to leverage the data generated during routine patient care. It formulates a more complete lexicon of evidence-based recommendations and support shared, ethical decision making by doctors with their patients. Diagnostic and therapeutic technologies continue to evolve rapidly, and both individual practitioners and clinical teams face increasingly complex ethical decisions. Unfortunately, the current state of medical knowledge does not provide the guidance to make the majority of clinical decisions on the basis of evidence. The present research infrastructure is inefficient and frequently produces unreliable results that cannot be replicated. Even randomized controlled trials (RCTs), the traditional gold standards of the research reliability hierarchy, are not without limitations. They can be costly, labor intensive, and slow, and can return results that are seldom generalizable to every patient population. Furthermore, many pertinent but unresolved clinical and medical systems issues do not seem to have attracted the interest of the research enterprise, which has come to focus instead on cellular and molecular investigations and single-agent (e.g., a drug or device) effects. For clinicians, the end result is a bit of a “data desert” when it comes to making decisions. The new research infrastructure proposed in this book will help the medical profession to make ethically sound and well informed decisions for their patients.

Practical Natural Language Processing

Sowmya Vajjala,Bodhisattwa Majumder,Anuj Gupta,Harshit Surana
Practical Natural Language Processing Book PDF

Author : Sowmya Vajjala,Bodhisattwa Majumder,Anuj Gupta,Harshit Surana
Publisher : O'Reilly Media
Page : 455 pages
File Size : 53,9 Mb
Release : 2020-06-17
Category : Computers
ISBN : 9781492054023

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Practical Natural Language Processing by Sowmya Vajjala,Bodhisattwa Majumder,Anuj Gupta,Harshit Surana Pdf

Many books and courses tackle natural language processing (NLP) problems with toy use cases and well-defined datasets. But if you want to build, iterate, and scale NLP systems in a business setting and tailor them for particular industry verticals, this is your guide. Software engineers and data scientists will learn how to navigate the maze of options available at each step of the journey. Through the course of the book, authors Sowmya Vajjala, Bodhisattwa Majumder, Anuj Gupta, and Harshit Surana will guide you through the process of building real-world NLP solutions embedded in larger product setups. You’ll learn how to adapt your solutions for different industry verticals such as healthcare, social media, and retail. With this book, you’ll: Understand the wide spectrum of problem statements, tasks, and solution approaches within NLP Implement and evaluate different NLP applications using machine learning and deep learning methods Fine-tune your NLP solution based on your business problem and industry vertical Evaluate various algorithms and approaches for NLP product tasks, datasets, and stages Produce software solutions following best practices around release, deployment, and DevOps for NLP systems Understand best practices, opportunities, and the roadmap for NLP from a business and product leader’s perspective

Healthcare Data Analytics

Chandan K. Reddy,Charu C. Aggarwal
Healthcare Data Analytics Book PDF

Author : Chandan K. Reddy,Charu C. Aggarwal
Publisher : CRC Press
Page : 756 pages
File Size : 50,5 Mb
Release : 2015-06-23
Category : Business & Economics
ISBN : 9781482232127

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Healthcare Data Analytics by Chandan K. Reddy,Charu C. Aggarwal Pdf

At the intersection of computer science and healthcare, data analytics has emerged as a promising tool for solving problems across many healthcare-related disciplines. Supplying a comprehensive overview of recent healthcare analytics research, Healthcare Data Analytics provides a clear understanding of the analytical techniques currently available

Analysis of Images, Social Networks and Texts

Wil M. P. van der Aalst,Vladimir Batagelj,Dmitry I. Ignatov,Michael Khachay,Valentina Kuskova,Andrey Kutuzov,Sergei O. Kuznetsov,Irina A. Lomazova,Natalia Loukachevitch,Amedeo Napoli,Panos M. Pardalos,Marcello Pelillo,Andrey V. Savchenko,Elena Tutubalina
Analysis of Images Social Networks and Texts Book PDF

Author : Wil M. P. van der Aalst,Vladimir Batagelj,Dmitry I. Ignatov,Michael Khachay,Valentina Kuskova,Andrey Kutuzov,Sergei O. Kuznetsov,Irina A. Lomazova,Natalia Loukachevitch,Amedeo Napoli,Panos M. Pardalos,Marcello Pelillo,Andrey V. Savchenko,Elena Tutubalina
Publisher : Springer Nature
Page : 366 pages
File Size : 49,7 Mb
Release : 2020-02-01
Category : Computers
ISBN : 9783030395759

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Analysis of Images, Social Networks and Texts by Wil M. P. van der Aalst,Vladimir Batagelj,Dmitry I. Ignatov,Michael Khachay,Valentina Kuskova,Andrey Kutuzov,Sergei O. Kuznetsov,Irina A. Lomazova,Natalia Loukachevitch,Amedeo Napoli,Panos M. Pardalos,Marcello Pelillo,Andrey V. Savchenko,Elena Tutubalina Pdf

This book constitutes the proceedings of the 8th International Conference on Analysis of Images, Social Networks and Texts, AIST 2019, held in Kazan, Russia, in July 2019. The 24 full papers and 10 short papers were carefully reviewed and selected from 134 submissions (of which 21 papers were rejected without being reviewed). The papers are organized in topical sections on general topics of data analysis; natural language processing; social network analysis; analysis of images and video; optimization problems on graphs and network structures; analysis of dynamic behaviour through event data.

Health Web Science

Kerstin Denecke
Health Web Science Book PDF

Author : Kerstin Denecke
Publisher : Springer
Page : 168 pages
File Size : 49,7 Mb
Release : 2015-08-31
Category : Medical
ISBN : 9783319205823

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Health Web Science by Kerstin Denecke Pdf

This book introduces the field of Health Web Science and presents methods for information gathering from written social media data. It explores the availability and utility of the personal medical information shared on social media platforms and determines ways to apply this largely untapped information source to healthcare systems and public health monitoring. Introducing an innovative concept for integrating social media data with clinical data, it addresses the crucial aspect of combining experiential data from social media with clinical evidence, and explores how the variety of available social media content can be analyzed and implemented. The book tackles a range of topics including social media’s role in healthcare, the gathering of shared information, and the integration of clinical and social media data. Application examples of social media for health monitoring, along with its usage in patient treatment are also provided. The book also considers the ethical and legal issues of gathering and utilizing social media data, along with the risks and challenges that must be considered when integrating social media data into healthcare choices. With an increased interest internationally in E-Health, Health 2.0, Medicine 2.0 and the recent birth of the discipline of Web Science, this book will be a valuable resource for researchers and practitioners investigating this emerging topic.

Hands-On Natural Language Processing with Python

Rajesh Arumugam,Rajalingappaa Shanmugamani
Hands On Natural Language Processing with Python Book PDF

Author : Rajesh Arumugam,Rajalingappaa Shanmugamani
Publisher : Packt Publishing Ltd
Page : 307 pages
File Size : 53,6 Mb
Release : 2018-07-18
Category : Computers
ISBN : 9781789135916

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Hands-On Natural Language Processing with Python by Rajesh Arumugam,Rajalingappaa Shanmugamani Pdf

Foster your NLP applications with the help of deep learning, NLTK, and TensorFlow Key Features Weave neural networks into linguistic applications across various platforms Perform NLP tasks and train its models using NLTK and TensorFlow Boost your NLP models with strong deep learning architectures such as CNNs and RNNs Book Description Natural language processing (NLP) has found its application in various domains, such as web search, advertisements, and customer services, and with the help of deep learning, we can enhance its performances in these areas. Hands-On Natural Language Processing with Python teaches you how to leverage deep learning models for performing various NLP tasks, along with best practices in dealing with today’s NLP challenges. To begin with, you will understand the core concepts of NLP and deep learning, such as Convolutional Neural Networks (CNNs), recurrent neural networks (RNNs), semantic embedding, Word2vec, and more. You will learn how to perform each and every task of NLP using neural networks, in which you will train and deploy neural networks in your NLP applications. You will get accustomed to using RNNs and CNNs in various application areas, such as text classification and sequence labeling, which are essential in the application of sentiment analysis, customer service chatbots, and anomaly detection. You will be equipped with practical knowledge in order to implement deep learning in your linguistic applications using Python's popular deep learning library, TensorFlow. By the end of this book, you will be well versed in building deep learning-backed NLP applications, along with overcoming NLP challenges with best practices developed by domain experts. What you will learn Implement semantic embedding of words to classify and find entities Convert words to vectors by training in order to perform arithmetic operations Train a deep learning model to detect classification of tweets and news Implement a question-answer model with search and RNN models Train models for various text classification datasets using CNN Implement WaveNet a deep generative model for producing a natural-sounding voice Convert voice-to-text and text-to-voice Train a model to convert speech-to-text using DeepSpeech Who this book is for Hands-on Natural Language Processing with Python is for you if you are a developer, machine learning or an NLP engineer who wants to build a deep learning application that leverages NLP techniques. This comprehensive guide is also useful for deep learning users who want to extend their deep learning skills in building NLP applications. All you need is the basics of machine learning and Python to enjoy the book.