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Bayesian Methodology: An overview with the help of R software
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
Application of statistical tools in biomedical domain: An overview with help of software
This book is an edited book from the papers of International Journal of Statistics and Medical Informatics authored by Editor, International of Statistics and Medical Informatics. It covers topics such as systematic review and meta-analysis, factor analysis, structural equation modelling and quantile regression in the field of biomedical domain. It also provides insight into the post hoc comparison, clinical trail data management and natural language processing
Generative AI – An Overview
Generative Artificial Intelligence, an Artificial Intelligence concept which is used to create own data which includes creating text, audio, video, images, programming codes and also advanced data structures such as protein structures. Before the Generative AI, Artificial Intelligence models used Machine learning models to predict pattern and structures. Generative AI models are widely being used in Business, healthcare, education and media sectors. Generative AI helps organizations to be more innovative, cost effective and efficient in their operations. Machine learning, Deep Learning, Large Language Models, transformers forms the basis for creating own data in Generative AI environment. Ge...
物聯網概論(第三版)
近年來人工智慧(AI) 應用無所不在，帶動大數據分析、雲端運算服務及物聯網(IoT)的科技升級，快速滲透到金融、零售、醫療、交通、保全、娛樂及製造等各式各樣產業。但是，迎接AI時代來臨，具備完善的大數據分析、雲端服務及資料運算平台，似乎不足以展現在AI領域的最大綜效，另一項融合新科技的創新能量「邊緣運算(edge computing)」已經悄悄在近年來蔓延發燒。隨著硬體功耗的增加及成本下降，物聯網的整合，它創造的大數據及透過AI理解的能力，嶄新時代必將來臨。 本書特色 1.本書以循序漸進的方式說明物聯網的起源、原理、技術與應用，讓讀者了解物聯網最新的觀念與應用。 2.本書於第2章說明物聯網在十大領域的應用(例如：智慧居家、智慧城市、穿戴式裝置等) 3.本書第4章詳細說明物聯網如何在5G時代與人工智慧、大數據結合應用。
Clinical Trial Management - an Overview
Clinical Trials word became a buzz word during this pandemic situation. It played a crucial role in developing vaccine to fight the pandemic. Experts from different fields contribute to the development of vaccine which includes (not limited) clinical researchers, health care providers, pharmaceutical industry, data managers, biostatisticians, data scientist and clinical trial programmers. Data collection, management, analysis and reporting also play an important role in helping decision makers in approving and rejecting the vaccine. This book provides an overview of clinical trial management process including protocol development, subject recruitment, professionals and organizations involved...
Digital Technologies – An overview of concepts, tools and techniques associated with it
Digital Technologies – An overview of concepts, tools and techniques associated with it Preface Digital technologies transformed the people’s day to day life and businesses organizations the way they work. It saved their time, accessibility and cost. It provided new opportunities, new markets, and new products to the organizations. Digital revolution started with the introduction of Computers, Internet, Mobile phones, Social media networks, Cloud computing, Big Data, Internet of Things, 3D Printing, Machine learning, Virtual reality, Natural Language Processing, Block Chain, Artificial Intelligence, Robotics and Quantum Computing. Digital technologies are so dynamic and it becomes diffic...
Python programming for Data Scientists
Python programming language is an open source programming language which can be used under different operating system. Python programming redefined the programming concepts with its important features like flexibility, adaptability and reusability of codes. Python programming language has numerous libraries or modules which helps the programmer to save their time. The book starts with the overview of basic Python topics such as data structures, data types, conditions and controls, functions, lists, file handling and handling external datasets and database connections. The book also covers the topics in data science such as graphical and chart visualization, statistical modeling, text mining ...
Forecasting models – an overview with the help of R software
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 t...
Deep Learning Models explored with help of Python Programming
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 w...
Designing and Conducting Clinical Trials – An overview
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 ...
