Big Data and Artificial Intelligence for Healthcare Applications
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Big Data and Artificial Intelligence for Healthcare Applications
Brault, Nicolas; Rashid, Shazia; Saxena, Ankur
Taylor & Francis Ltd
10/2024
274
Mole
9780367554972
Pré-lançamento - envio 15 a 20 dias após a sua edição
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Part I: Conceptual. 1. Introduction to Big Data. 2. Introduction to Machine Learning. Part II: Application. 3. Machine Learning in Clinical Trials. 4. Deep Learning and Its Biological and Biomedical Applications. 5. Applications of Machine Learning Algorithms to Cancer Data. 6. Pancreatic Cancer Detection by an Integrated Level Set-Based Deep Learning Model. 7. Early and Precision-Oriented Detection of Cervical Cancer. 8. Transformation of mHealth in Society. 9. Artificial Intelligence and Deep Learning for Medical Diagnosis and Treatment. Part III: Ethics. 10. Ethical Issues and Challenges with Artificial Intelligence in Healthcare. 11. Epistemological Issues and Challenges with Artificial Intelligence in Healthcare.
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
Mobile Health;Clinical Trial;Data Management;Machine Learning;Data Mining;Pattern Recognition;mHealth Services;Healthcare applications;Teleological Ethics;Big data analytics;NGS Data;Artificial Intelligence;TCGA;mHealth Apps;Clinical trial data management;Bayes Error;Deep Learning Models;SVM Ensemble;SVM;mHealth Devices;Deep Learning Algorithms;CNN Model;Convolutional Layers;Building Classification Models;Deep Learning;Ml Algorithm;Cervical Cancer;RNA Protein Interaction;Single Cell RNA Seq;Level Set Formulation;Digital Breast Tomosynthesis;Multiple Linear Regression;Lower Loss Values;Smart Phone;Smartphones
Part I: Conceptual. 1. Introduction to Big Data. 2. Introduction to Machine Learning. Part II: Application. 3. Machine Learning in Clinical Trials. 4. Deep Learning and Its Biological and Biomedical Applications. 5. Applications of Machine Learning Algorithms to Cancer Data. 6. Pancreatic Cancer Detection by an Integrated Level Set-Based Deep Learning Model. 7. Early and Precision-Oriented Detection of Cervical Cancer. 8. Transformation of mHealth in Society. 9. Artificial Intelligence and Deep Learning for Medical Diagnosis and Treatment. Part III: Ethics. 10. Ethical Issues and Challenges with Artificial Intelligence in Healthcare. 11. Epistemological Issues and Challenges with Artificial Intelligence in Healthcare.
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
Mobile Health;Clinical Trial;Data Management;Machine Learning;Data Mining;Pattern Recognition;mHealth Services;Healthcare applications;Teleological Ethics;Big data analytics;NGS Data;Artificial Intelligence;TCGA;mHealth Apps;Clinical trial data management;Bayes Error;Deep Learning Models;SVM Ensemble;SVM;mHealth Devices;Deep Learning Algorithms;CNN Model;Convolutional Layers;Building Classification Models;Deep Learning;Ml Algorithm;Cervical Cancer;RNA Protein Interaction;Single Cell RNA Seq;Level Set Formulation;Digital Breast Tomosynthesis;Multiple Linear Regression;Lower Loss Values;Smart Phone;Smartphones
