Handbook on Intelligent Healthcare Analytics. Группа авторов

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      1 Chapter 1Figure 1.1 Knowledge engineering.Figure 1.2 Knowledge as modelling process.Figure 1.3 KBE.

      2 Chapter 2Figure 2.1 Traditional Bayesian Neural Network disaster prediction from the data...Figure 2.2 Proposed system for predicting disaster using improved Bayesian hidde...Figure 2.3 Total number of disaster analysis using improved Bayesian Markov chai...Figure 2.4 Changes from various impacts from natural disaster.Figure 2.5 Economic damage changes a prediction analysis.Figure 2.6 Boxplot view of natural disaster on various entity.

      3 Chapter 3Figure 3.1 Dimensions of big data.Figure 3.2 Big data value creation flow.Figure 3.3 Different sources of healthcare data.Figure 3.4 Knowledge discovery process of big data in healthcare.

      4 Chapter 4Figure 4.1 Architecture diagram.Figure 4.2 Functional block diagram.Figure 4.3 Storage block.Figure 4.4 Reporting block.Figure 4.5 Analysis block.Figure 4.6 Management block.Figure 4.7 Use case diagram.Figure 4.8 Sequence diagram.Figure 4.9 Class diagram.Figure 4.10 Cases of patients.Figure 4.11 Notifications of medicines to endpoints.Figure 4.12 Admin dashboard.

      5 Chapter 5Figure 5.1 Process of knowledge engineering.Figure 5.2 Data science and knowledge engineering.

      6 Chapter 6Figure 6.1 Conceptual healthcare stock prediction system.Figure 6.2 Overview of business intelligence and analytics framework.Figure 6.3 Illustration of healthcare stock prediction system.Figure 6.4 Prediction of the closing price using LR.Figure 6.5 Prediction of the closing price using ARIMA.Figure 6.6 Prediction of the closing price using LSTM.Figure 6.7 Prediction of the closing price using LR.Figure 6.8 Prediction of the closing price using ARIMA.Figure 6.9 Prediction of the closing price using LSTM.Figure 6.10 Prediction of the closing price using LR.Figure 6.11 Prediction of the closing price using ARIMA.Figure 6.12 Prediction of the closing price using LSTM.Figure 6.13 Prediction of the closing price using LR.Figure 6.14 Prediction of the closing price using ARIMA.Figure 6.15 Prediction of the closing price using LSTM.Figure 6.16 Prediction of the closing price using LR.Figure 6.17 Prediction of the closing price using ARIMA.Figure 6.18 Prediction of the closing price using LSTM.Figure 6.19 Prediction of the closing price using LR.Figure 6.20 Prediction of the closing price using ARIMA.Figure 6.21 Prediction of the closing price using LSTM.Figure 6.22 Prediction of the closing price using LR.Figure 6.23 Prediction of the closing price using ARIMA.Figure 6.24 Prediction of the closing price using LSTM.Figure 6.25 Prediction of the closing price using LR.Figure 6.26 Prediction of the closing price using ARIMA.Figure 6.27 Prediction of the closing price using LSTM.Figure 6.28 Prediction of the closing price using LR.Figure 6.29 Prediction of the closing price using ARIMA.Figure 6.30 Prediction of the closing price using LSTM.Figure 6.31 Prediction of the closing price using LR.Figure 6.32 Prediction of the closing price using ARIMA.Figure 6.33 Prediction of the closing price using LSTM.

      7 Chapter 7Figure 7.1 Block diagram for smart diabetes prediction.Figure 7.2 Decision tree diagram for attribute age.Figure 7.3 Categorized into carbohydrate, protein, and fat.Figure 7.4 Percentages of each category of persons identified from analyzed valu...Figure 7.5 Conceptual diagram for prediction of ADHD/LD.Figure 7.6 Decision tree for classification of learners.Figure 7.7 Classification of learners.Figure 7.8 Heart disease using naïve bayes classifier.Figure 7.9 ECC k(binary) FSM.Figure 7.10 k-NAF ECC processor.Figure 7.11 k-NAF FSM.Figure СКАЧАТЬ