Practical Data Analytics for Innovation in Medicine

Part I: Historical Perspective and the Issues of Concern for Health Care Delivery in the 21st Century<br>1. History of Medical Health Care Delivery & Basic Medical Research<br>2. "Things That Matter !!!" - Why This Book?<br>3. Biomedical Informatics<br>4. Access to Data for Analytics – the ‘Biggest Issue’ in Medical and Healthcare Predictive Analytics<br>5. Regulatory Measures – Agencies, and Data Issues in Medicine and Healthcare<br>6. Personalized Medicine<br>7. Patient-Directed Healthcare<br>8. OMICS or MULTIOMICS<br>9. Challenges and Considerations of AI and Genomics<br><br>Part II: Practical Step-by-Step Tutorials and Case Studies<br>TUTORIAL A Case Study: Imputing Medical Specialty Using Data Mining Models<br>TUTORIAL AA: VOC for Cancer Detection / Prediction<br>TUTORIAL B Case Study: Using Association Rules of Investigate Characteristics of Hospital Readmissions TUTORIAL BB Case Study: COVID-19 Descriptive Analysis Around the World<br>TUTORIAL C Constructing Decision Trees for Medicare Claims Using R and Rattle<br>TUTORIAL D Predictive and Prescriptive Analytics for Optimal Decisioning: Hospital Readmission Risk Mitigation<br>TUTORIAL E Obesity Group: Predicting Medicine and Conditions That Achieved the Greatest Weight Loss in a Group of Obese/Morbidly Obese Patients<br>TUTORIAL F1 Obesity Individual: Predicting Best Treatment or an Individual from Portal Data at a Clinic<br>TUTORIAL F2 Obesity Individual: Automatic Binning of Continuous Variables and WoE to Produce a Better Model than the "Hand Binned" Stepwise Regression Model<br>TUTORIAL G Resiliency Study for First- and Second-Year Medical Residents<br>TUTORIAL H Medicare Enrollment Analysis Using Visual Data Mining<br>TUTORIAL I Case Study: Detection of Stress-Induced Ischemia in Patients with Chest Pain "Rule-Out ACS" Protocol<br>TUTORIAL J1 Predicting Survival or Mortality for Patients with Disseminated Intravascular Coagulation and/or Critical illnesses<br>TUTORIAL J2 Decisioning for DIC<br>TUTORIAL K Predicting Allergy Symptoms<br>TUTORIAL L Exploring Discrete Database Networks of TriCare Health Data Using R and Shiny<br>TUTORIAL M Schistosomiasis Data from WHO<br>TUTORIAL N The Poland Medical Bundle<br>TUTORIAL O Medical Advice Acceptance Prediction<br>TUTORIAL P Using Neural Network Analysis to Assist in Classifying Neuropsychological Data<br>TUTORIAL Q Developing Interactive Decision Trees using Inpatient Claims (with SAS Enterprise Miner)<br>TUTORIAL R Divining Healthcare Charges for Optimal Health Benefits Under the Affordable Care Act<br>TUTORIAL S Availability of Hospital Beds for Newly Admitted Patients: The Impact of Environmental Services on Hospital Throughput<br>TUTORIAL T Predicting Vascular Thrombosis: Comparing Predictive Analytic Models and Building an Ensemble Model for "Best Prediction"<br>TUTORIAL U Predicting Breast Cancer Diagnosis Using Support Vector Machines<br>TUTORIAL V Heart Disease: Evaluating Variables That Might Have an Effect on Cholesterol Level (Using Recode of Variables Function) TUTORIAL W Blood Pressure Predictive Factors<br>TUTORIAL X Gene Search and the Related Risk Estimates: A Statistical Analysis of Prostate Cancer Data<br>TUTORIAL Y Ovarian Cancer Prediction via Proteomic Mass Spectrometry<br>TUTORIAL Z Influence of Stent Vendor Representatives in the Catheterization Lab<br><br>Part III: Practical Solutions and Advanced Topics in Administration and Delivery of Health Care Including Practical Predictive Analytics for Medicine<br>1. Challenges for Healthcare Administration and Delivery: Integrating Predictive and Prescriptive Modeling into Personalized Health Care<br>2. Challenges of Medical Research for the Remainder of the 21st Century<br>3. Introduction to the Cornerstone Chapters of this Book, Chapters 12 -15: The "Three Processes": Quality Control, Predictive Analytics, and Decisioning<br>4. The Nature of Insight from Data and Implications for Automated Decisioning: Predictive and Prescriptive Models, Decisions, and Actions<br>5. Decisioning Systems (Platforms) Coupled with Predictive Analytics in a Real Hospital Setting - A Model for the World<br>6. The Latest in Predictive and Prescriptive Analytics<br>7. The Coming Standard for a Data Model – OMOP (Observational Medical Outcomes Partnership) as per Observational Health Data Sciences and Informatics (OHDS) at University of California-Irvine<br>8. A Real Case Study of GLAUCOMA (eye disease) and suggested PREDICTIVE MODELING for identifying individual patient predictions of best treatment with high accuracy<br>9. Analytics Architectures for the 21st Century<br>10. Causation and How This ‘Cutting Edge Concept’ Works with Predictive Analytics and Prescriptive Analytics (Decisioning)<br>11. 21st Century Healthcare and Wellness: Getting the Health Care Delivery System That Meets Global Needs