The Power of Prediction in Health Care: A Step-by-step Guide to Data Science in Health Care
Rafiq Muhammad
This audiobook is narrated by a digital voice.
In this comprehensive guide, I offer valuable insights tailored for data science graduate students and early career researchers stepping into the dynamic world of data science.
My distinctive...
Location:
United States
Description:
This audiobook is narrated by a digital voice. In this comprehensive guide, I offer valuable insights tailored for data science graduate students and early career researchers stepping into the dynamic world of data science. My distinctive background merges clinical medicine with data science expertise, holding an MBBS, an MBA in Healthcare, and a Ph.D. in Artificial Intelligence in Healthcare. This diverse foundation allows me to bridge the gap between these two fields. During my early career and Ph.D. journey in data science, I encountered and surmounted the challenges of navigating complex data analysis and machine learning, despite lacking a computer science background. Today, I'm excited to share the knowledge and experiences I've gained with newcomers in the field. Within the pages of this book, you'll discover a structured, step-by-step approach to conceptualizing, designing, and executing data science projects within the healthcare domain. Tailored for graduate students and early career researchers, this educational journey equips you with practical skills and knowledge to harness the remarkable potential of data science in healthcare. This book offers: • A systematic guide for planning and executing data science projects in healthcare. • A beginner-friendly structure designed to facilitate project development. • Direct links to valuable resources and open-source tools for creating and executing AI projects in healthcare. • Access to freely available healthcare databases. • Real-world case studies illustrating the construction of data science projects. Whether you're a healthcare professional looking to expand your skill set or a budding data scientist seeking to make a meaningful impact in the healthcare sector, 'The Power of Prediction in Health Care' is an invaluable companion for unlocking the potential of data science in healthcare. Filled with practical examples and actionable advice drawn from real-world scenarios, this book empowers you to make data-driven decisions that enhance patient outcomes and reshape the healthcare landscape. Duration - 3h 2m. Author - Rafiq Muhammad. Narrator - Digital Voice Mike G. Published Date - Monday, 20 January 2025. Copyright - © 2024 Rafiq Muhammad ©.
Language:
English
Title
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Unique Features and Structure of This Book
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Target Audience of This Book
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Why I Wrote This Book?
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Chapter 1. Introduction
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Definition of AI and Data Science in Healthcare
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Historical Perspective of AI in Healthcare
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Importance of AI and Data Science in Healthcare
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Career in Data Science and Artificial Intelligence in Healthcare
Duration:00:01:14
Benefits of Career in Data Science and Artificial Intelligence in Healthcare
Duration:00:02:31
Chapter 2. Fundamentals of Data Science in Healthcare
Duration:00:01:09
Data Collection and Integration
Duration:00:03:26
Types of Data
Duration:00:03:38
Data Sources
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Data Quality
Duration:00:01:52
Data Collection
Duration:00:01:22
Data Preprocessing and Cleaning
Duration:00:04:27
Data Exploration and Visualization
Duration:00:04:08
Predictive Modeling
Duration:00:00:38
Machine Learning Algorithms
Duration:00:00:21
Feature Selection and Engineering
Duration:00:00:19
Ethical Considerations and Privacy
Duration:00:00:23
Interpretability and Explainability
Duration:00:00:17
Validation and Evaluation
Duration:00:00:23
Clinical Integration and Decision Support
Duration:00:00:19
Continuous Learning and Improvement
Duration:00:00:25
Types of AI
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Types of Machine learning algorithms
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Performance Metrics and Evaluation Methods
Duration:00:08:35
Chapter 3. Steps in Data Analysis and AI Model Development
Duration:00:00:32
Problem Definition
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Data Collection and Data Cleaning
Duration:00:01:00
Exploratory Data Analysis
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Feature Selection and Feature Engineering
Duration:00:01:13
Data Splitting
Duration:00:00:30
Model Selection
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Model Development
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Model Evaluation
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Model Interpretation
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Model Deployment
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Model Monitoring and Maintenance
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Ethical Considerations
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Documentation
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Chapter 4. Tools and Resources for Healthcare Data Science
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ChatGPT-Assisted Data Science
Duration:00:03:09
Free Datasets for Healthcare Data Science
Duration:00:05:03
Programming Languages
Duration:00:06:02
Data Visualization Tools
Duration:00:05:59
Machine Learning Frameworks
Duration:00:02:32
Big Data Tools
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Online AI and ML Tools
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Healthcare Data Standards
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Chapter 5. Case study of Hospital Readmission Prediction with R
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Chapter 6. Applications of AI and Data Science in Clinical Decision Making
Duration:00:00:40
Clinical Decision Support Systems
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Diagnostic Imaging and Radiology
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Precision Medicine and Genomics
Duration:00:00:43
AI in Mental Health
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AI in Clinical Trials, Drug Discovery and Development
Duration:00:01:06
Electronic Health Records and Clinical Workflows
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Chapter 7. Applications of AI and Data Science in Healthcare Operations
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Telemedicine and Remote Patient Care
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Healthcare Supply Chain and Logistics
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Fraud Detection and Prevention
Duration:00:00:51
Disease Surveillance/Public Health
Duration:00:00:50
Chapter 8. Ethical Considerations and Challenges
Duration:00:00:49
Bias and Fairness in AI Models
Duration:00:01:30
Privacy and Data Security
Duration:00:02:12
Impact on Healthcare Workforce
Duration:00:03:02
Legal and Regulatory Issues
Duration:00:03:28
Patient Safety and Healthcare Quality
Duration:00:01:25
Chapter 9. Future Directions and Challenges
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About The Author
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10. References
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