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Author: EDITOR IJSMI Publisher: createspace ISBN: 1725921227 Category : Medical Languages : en Pages : 67
Book Description
This book intends to provide an overview of biostatistics concepts and methodology through the use of statistical software. It helps clinicians, health care and biomedical professionals who need to have basic knowledge of biostatistics as they come across clinical data related to patient, drug and dosage requirement, treatment modalities in day to day life and they are required to take clinical and health care decisions based on the data. This book covers basic concepts involved in the field of Biostatistics such as descriptive statistics, inferential statistics, correlation and regression along with the advanced concepts such as factor analysis, cluster analysis, discriminant analysis and survival analysis. Each topic is explained with the help of R statistical package (open source package). One important note that the book will not discuss about the formulas and equations involved in the statistical concepts and the author assumes that the readers have basic understanding of excel as the sample dataset is used in the book are mostly excel based datasets and also have some clinical background.
Author: EDITOR IJSMI Publisher: createspace ISBN: 1725921227 Category : Medical Languages : en Pages : 67
Book Description
This book intends to provide an overview of biostatistics concepts and methodology through the use of statistical software. It helps clinicians, health care and biomedical professionals who need to have basic knowledge of biostatistics as they come across clinical data related to patient, drug and dosage requirement, treatment modalities in day to day life and they are required to take clinical and health care decisions based on the data. This book covers basic concepts involved in the field of Biostatistics such as descriptive statistics, inferential statistics, correlation and regression along with the advanced concepts such as factor analysis, cluster analysis, discriminant analysis and survival analysis. Each topic is explained with the help of R statistical package (open source package). One important note that the book will not discuss about the formulas and equations involved in the statistical concepts and the author assumes that the readers have basic understanding of excel as the sample dataset is used in the book are mostly excel based datasets and also have some clinical background.
Author: Editor IJSMI Publisher: ISBN: 9781723712074 Category : Languages : en Pages : 68
Book Description
This book intends to provide an overview of biostatistics concepts and methodology through the use of statistical software. It helps clinicians, health care and biomedical professionals who need to have basic knowledge of biostatistics as they come across clinical data related to patient, drug and dosage requirement, treatment modalities in day to day life and they are required to take clinical and health care decisions based on the data. This book covers basic concepts involved in the field of Biostatistics such as descriptive statistics, inferential statistics, correlation and regression along with the advanced concepts such as factor analysis, cluster analysis, discriminant analysis and survival analysis. Each topic is explained with the help of R statistical package (open source package). One important note that the book will not discuss about the formulas and equations involved in the statistical concepts. Author assumes that the readers have basic understanding of excel, as the sample datasets used in the book are mostly excel based datasets and also have some clinical background.
Author: Editor Ijsmi Publisher: Essential of Biostatistics: An ISBN: 9781729293577 Category : Education Languages : en Pages : 70
Book Description
This book is the second in series of Essentials of Biostatistics wherein the first book provided the overview of Biostatistics concepts and methods with the help of R software. The current book will focus on the use of SAS software as most of the users in the biomedical field uses SAS because of its recognition especially the United States government agencies like Food and Drug Administration (FDA).The important note is that the book will not repeat the biostatistics concepts and methodology explained in the first book and it will concentrate mainly on the SAS software part and it is strongly advisable to use both books get a complete idea of biostatistical concepts and methodology especially for the beginners. EditorInternational Journal of Statistics and Medical Informatics (IJSMI)
Author: Editor IJSMI Publisher: International Journal Statistics and Medical Informatics ISBN: 109293989X Category : Business & Economics Languages : en Pages : 75
Book Description
Bayesian methodology differs from traditional statistical methodology which involves frequentist approach. Bayesian methodology was introduced by Thomas Bayes (Statistician and minister at the Presbyterian Chapel) during the 18th Century. Bayesian methodology is now widely being used due to its simple, straightforward and interpretable characteristics of probability values and the efficiency of modern day computer systems. Bayesian methodology is now being used in the field of clinical research, clinical trials, epidemiology, econometrics, statistical process control, marketing research and statistical mechanics. It also used in the emerging field such as data science (machine learning and deep learning) and big data analytics. The book provides an overview of Bayesian methodology, its uses in different fields with the help of R statistical open source software. Editor International Journal of Statistics and Medical Informatics www.ijsmi.com/book.php
Author: Editor IJSMI Publisher: IJSMI ISBN: 1790122627 Category : Computers Languages : en Pages : 78
Book Description
This book intends to provide an overview of Machine Learning and its algorithms & models with help of R software. Machine learning forms the basis for Artificial Intelligence which will play a crucial role in day to day life of human beings in the near future. A basic understanding of machine learning is required, as its application is widely seen in different fields such as banks and financial sectors, manufacturing, aviation, transportation and medical field. The book covers machine learning classification algorithms such as K-Nearest Neighborhood, Naïve Bayes, Decision Trees and also Artificial Neural Networks and Support Vector Machines. It is recommended to refer author’s book on Application of Statistical Tools in Biomedical Domain: An Overview with Help of Software (https://www.amazon.com/dp/1986988554) and Essentials of Bio-Statistics: An overview with the help of Software https://www.amazon.com/dp/B07GRBXX7D if you need to familiarize yourself with the basic statistical knowledge. Editor International Journal of Statistics and Medical Informatics www.ijsmi.com/book.php Amazon link https://www.amazon.com/dp/1790122627 (Paper Back) https://www.amazon.com/dp/B07KQSN447 (Kindle Edition)
Author: Editor IJSMI Publisher: international Journal of Statistics and Medical Informatics ISBN: 1081552808 Category : Mathematics Languages : en Pages : 101
Book Description
Forecasting models – an overview with the help of R software Preface Forecasting models involves predicting the future values of a particular series of data which is mainly based on the time domain. Forecasting models are widely used in the fields such as financial markets, demand for a product and disease outbreak. The objective of the forecasting model is to reduce the error in the forecasting. Most of the Forecasting models are based on time series, a statistical concept which involves Moving Averages, Auto Regressive Integrated Moving Averages (ARIMA), Exponential smoothing and Generalized Auto Regressive Conditional Heteroscedastic (GARCH) Models. Forecasting models which we deal in this book will be explorative forecasting models which take into account the past data to predict the future values. Current day forecasting models uses advanced techniques such as Machine Learning and Deep Learning Algorithms which are more robust and can handle high volume of data. This book starts with the overview of forecasting and time series concepts and moves on to build forecasting models using different time series models. Examples related to forecasting models which are built based on Machine learning also covered. The book uses R statistical software package, an open source statistical package to build the forecasting models. Editor International Journal of Statistics and Medical Informatics www.ijsmi.com/book.php https://www.amazon.co.uk/dp/B07VFY53B1
Author: Lisa M. Sullivan Publisher: Jones & Bartlett Publishers ISBN: 0763795321 Category : Education Languages : en Pages : 329
Book Description
With a presentation style that is clear and straightforward, the text uses examples that are real, relevant, and manageable in size so that students can focus on applications rather than become overwhelmed by computations. This text is just one offering in Jones and Bartlett's unique Essential Public Health Series. Important Notice: The digital edition of this book is missing some of the images or content found in the physical edition.
Author: Editor IJSMI Publisher: International Journal of Statistics and Medical Informatics ISBN: Category : Young Adult Nonfiction Languages : en Pages : 102
Book Description
This is the second book in the Deep Learning models series by the author. Deep learning models are widely used in different fields due to its capability to handle large and complex datasets and produce the desired results with more accuracy at a greater speed. In Deep learning models, features are selected automatically through the iterative process wherein the model learns the features by going deep into the dataset and selects the features to be modeled. In the traditional models the features of the dataset needs to be specified in advance. The Deep Learning algorithms are derived from Artificial Neural Network concepts and it is a part of broader Machine Learning Models. The book starts with the Introduction part which is adopted from Author’s Deep Learning Models and its application: An overview with the help of R software book and move on to the Python’s important data processing packages such Numpy, and Pandas. Book then explores the Deep Learning models with the help of packages such as Pytorch, Tensor Flow and Keras and their applications in image processing, stock market prediction, recommender systems and natural language processing. Editor International Journal of Statistics and Medical Informatics www.ijsmi.com/book.php ISBN: 9798558877953 E-Books: https://www.amazon.com/dp/B08MQTM1ZP Paperbacks: https://www.amazon.com/dp/B08MSQ3R8R
Author: Editor IJSMI Publisher: International Journal of Statistics and Medical Informatics ISBN: 1096489082 Category : Medical Languages : en Pages : 52
Book Description
Clinical trials can be defined as an experiment which is conducted in a controlled environment to test the efficacy of drugs, procedures, methodology before bringing into the public domain. The clinical trials started in 2nd century BC by Daniel & King Nebuchadnezzar. Formal recorded therapeutic clinical trial was started way back in 1537 AD by a Surgeon. Current clinical trials include clear guidelines, adhering to regulatory requirements, getting consent from the patients, ensuring safety of the patients, adopting ethical practices, close monitoring of the trials and using advanced statistical tools to analyze and report the findings. Advancement in technology such as cloud computing, big data analytics, machine learning algorithms, data base management and advanced statistical software helped to transform the different stages of clinical trials - the data collection, data storage, data monitoring, data management and data analysis. This book provides an overview of clinical trials, different phases & types of clinical trial, randomization, blinding, allocation, ethical issues, protocol, data collection forms, data management, data analysis and reporting of the clinical trial. It is recommended to refer author’s book on Application of Statistical Tools in Biomedical Domain: An Overview with Help of Software (https://www.amazon.com/dp/1986988554) and Essentials of Bio-Statistics: An overview with the help of Software https://www.amazon.com/dp/B07GRBXX7D if you need to familiarize yourself with the basic statistical knowledge.
Author: EDITOR IJSMI
Author: EDITOR IJSMI
Author: Editor IJSMI
Author: Editor Ijsmi
Author: Editor IJSMI
Author: Editor IJSMI
Author: Editor IJSMI
Author: Lisa Marie Sullivan
Author: Lisa M. Sullivan
Author: Editor IJSMI
Author: Editor IJSMI