Exploratory Data Analytics for Healthcare
portes grátis
Exploratory Data Analytics for Healthcare
Kumar, R. Lakshmana; Balamurugan, B.; Shankar, Achyut; Indrakumari, R.
Taylor & Francis Ltd
12/2021
292
Dura
Inglês
9780367506919
15 a 20 dias
530
Descrição não disponível.
Chapter 1. Visual Analytics: Scopes & Challenges. Chapter 2. Statistical Methods and Applications: A Comprehensive Reference for the Healthcare Industry. Chapter 3. Machine Learning Algorithms for Healthcare Data Analytics. Chapter 4. A Review of Challenges and Opportunities in Machine Learning for Healthcare. Chapter 5. Digitalizing the Health Records Using Machine Learning Algorithms. Chapter 6. Interactive Visualization for Understanding and Analyzing Medical Data. Chapter 7. Heart Disease Prediction Using Tableau. Chapter 8. A Deep Learning Framework Using AlexNet for Early Detection of Pancreatic Cancer. Chapter 9. Applications of the Map-Reduce Programming Framework to Clinical Big Data Analysis: Current Landscape and Future Trends. Chapter 10. An Investigation of Different Machine Learning Approaches for Healthcare Analytics. Chapter 11. The Potential of Machine Learning for Clinical Predictive Analytics. Chapter 12. Predictive Analytics in Healthcare Using Machine Learning Tools and Techniques. Chapter 13. A Collective Study of Machine Learning (ML) Algorithms and Its Impact on Various Facets of Healthcare.
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
UCI Repository;Big Data Analytics;Support Vector Machine;Data Visualization;Machine Learning Algorithm;Machine Learning;EHR;Multivariate Temporal Data;Semi-supervised Learning;caleydo Stratemex Tool;Ml Model;Artifical Intelligence;Random Forest;Random Forest Algorithm;KNN Algorithm;Smart Healthcare;Big Data;Healthcare Data Analytics;Bayes Algorithm;Semi-supervised Learning Algorithms;Unsupervised Ml;Supervise Ml;Rounded Corner Rectangle;Personalized Medicine;Hadoop Map Reduce;Subspace Clustering;Big Data Solutions;Hadoop Map Reduce Framework;CSV File;Ml Algorithm;DICOM File
Chapter 1. Visual Analytics: Scopes & Challenges. Chapter 2. Statistical Methods and Applications: A Comprehensive Reference for the Healthcare Industry. Chapter 3. Machine Learning Algorithms for Healthcare Data Analytics. Chapter 4. A Review of Challenges and Opportunities in Machine Learning for Healthcare. Chapter 5. Digitalizing the Health Records Using Machine Learning Algorithms. Chapter 6. Interactive Visualization for Understanding and Analyzing Medical Data. Chapter 7. Heart Disease Prediction Using Tableau. Chapter 8. A Deep Learning Framework Using AlexNet for Early Detection of Pancreatic Cancer. Chapter 9. Applications of the Map-Reduce Programming Framework to Clinical Big Data Analysis: Current Landscape and Future Trends. Chapter 10. An Investigation of Different Machine Learning Approaches for Healthcare Analytics. Chapter 11. The Potential of Machine Learning for Clinical Predictive Analytics. Chapter 12. Predictive Analytics in Healthcare Using Machine Learning Tools and Techniques. Chapter 13. A Collective Study of Machine Learning (ML) Algorithms and Its Impact on Various Facets of Healthcare.
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
UCI Repository;Big Data Analytics;Support Vector Machine;Data Visualization;Machine Learning Algorithm;Machine Learning;EHR;Multivariate Temporal Data;Semi-supervised Learning;caleydo Stratemex Tool;Ml Model;Artifical Intelligence;Random Forest;Random Forest Algorithm;KNN Algorithm;Smart Healthcare;Big Data;Healthcare Data Analytics;Bayes Algorithm;Semi-supervised Learning Algorithms;Unsupervised Ml;Supervise Ml;Rounded Corner Rectangle;Personalized Medicine;Hadoop Map Reduce;Subspace Clustering;Big Data Solutions;Hadoop Map Reduce Framework;CSV File;Ml Algorithm;DICOM File
