Recent trends in artificial intelligence towards a smart world applications in industries and sectors Rajeev Arya, Subhash Chander Sharma, Ajit Kumar Verma …[and another].

Colaborador(es): Idioma: Inglés Series Detalles de publicación: Singapore Springe 2024Edición: 1a. EdDescripción: 431 PaginasISBN:
  • 9789819767892
  • 9789819767908
Tema(s):
Contenidos:
Intro -- Preface -- Contents -- Editors and Contributors -- 1 AI-Driven Cognitive Radio Networks for Transforming Industries and Sectors Towards a Smart World -- 1.1 Introduction -- 1.2 Integration of AI in CRNs -- 1.3 The Potential for AI-Driven CRNs to Revolutionize a Variety of Industries -- 1.4 Cognitive Radio Networks and Artificial Intelligence -- 1.4.1 Cognitive Radio Networks: An Overview -- 1.4.2 Artificial Intelligence: An Overview -- 1.5 Artificial Intelligence in Cognitive Radio Networks -- 1.5.1 Artificial Intelligence Methodologies to Cognitive Radios Networks 1.5.2 Machine Learning Approaches to Cognitive Radio Networks -- 1.6 Applications of CRNs and AI-Driven CRNs in Sectors of Smart World -- 1.6.1 Application of the Cognitive Radio Networks -- 1.6.2 Application of the AI-Driven CRNs -- 1.7 Challenges and Solutions of AI-Driven CRNs -- 1.8 Future Trends AI-Driven CRNs and Anticipated Impacts on Industries and Sectors -- 1.9 Conclusion -- References -- 2 Beyond the Code: Bridging Ethical and Practical Gaps in Data Privacy for AI-Enhanced Healthcare Systems -- 2.1 Introduction -- 2.2 The Pivotal Role of Patient Data -- 2.3 Background 2.4 Types of Healthcare Data -- 2.5 Evolution to Digital Health Records -- 2.6 Challenges in AI for Healthcare Systems -- 2.6.1 Data Privacy and Security -- 2.6.2 Bias and Fairness thical -- 2.6.3 Reliability and Accountability -- 2.7 AI in Diagnostic Imaging: Transforming Radiology with Deep Learning -- 2.7.1 Introduction to AI in Diagnostic Imaging -- 2.7.2 The Role of AI in Radiology -- 2.7.3 Advanced Applications of AI in Radiology -- 2.7.4 Integration of AI in Radiological Workflows -- 2.7.5 Addressing Challenges in AI-Driven Radiology 2.8 Case Study: AI-Powered Detection of Pulmonary Diseases -- 2.9 Introduction to AI in Patient Monitoring -- 2.10 Case Study: AI for Enhanced Patient Monitoring and Care -- 2.11 Introduction to AI in Drug Discovery -- 2.11.1 AI's Impact on the Drug Discovery Process -- 2.11.2 The Role of AI in Personalized Medicine -- 2.11.3 Overcoming Challenges in Drug Discovery with AI -- 2.11.4 AI Collaborations in Pharma -- 2.12 Case Study: Accelerating Alzheimer's Drug Discovery -- 2.13 Ethical Debates and Perspectives in AI-Enhanced Healthcare -- 2.14 AI's Broad Impact Across Healthcare Sectors
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Intro -- Preface -- Contents -- Editors and Contributors -- 1 AI-Driven Cognitive Radio Networks for Transforming Industries and Sectors Towards a Smart World -- 1.1 Introduction -- 1.2 Integration of AI in CRNs -- 1.3 The Potential for AI-Driven CRNs to Revolutionize a Variety of Industries -- 1.4 Cognitive Radio Networks and Artificial Intelligence -- 1.4.1 Cognitive Radio Networks: An Overview -- 1.4.2 Artificial Intelligence: An Overview -- 1.5 Artificial Intelligence in Cognitive Radio Networks -- 1.5.1 Artificial Intelligence Methodologies to Cognitive Radios Networks 1.5.2 Machine Learning Approaches to Cognitive Radio Networks -- 1.6 Applications of CRNs and AI-Driven CRNs in Sectors of Smart World -- 1.6.1 Application of the Cognitive Radio Networks -- 1.6.2 Application of the AI-Driven CRNs -- 1.7 Challenges and Solutions of AI-Driven CRNs -- 1.8 Future Trends AI-Driven CRNs and Anticipated Impacts on Industries and Sectors -- 1.9 Conclusion -- References -- 2 Beyond the Code: Bridging Ethical and Practical Gaps in Data Privacy for AI-Enhanced Healthcare Systems -- 2.1 Introduction -- 2.2 The Pivotal Role of Patient Data -- 2.3 Background 2.4 Types of Healthcare Data -- 2.5 Evolution to Digital Health Records -- 2.6 Challenges in AI for Healthcare Systems -- 2.6.1 Data Privacy and Security -- 2.6.2 Bias and Fairness thical -- 2.6.3 Reliability and Accountability -- 2.7 AI in Diagnostic Imaging: Transforming Radiology with Deep Learning -- 2.7.1 Introduction to AI in Diagnostic Imaging -- 2.7.2 The Role of AI in Radiology -- 2.7.3 Advanced Applications of AI in Radiology -- 2.7.4 Integration of AI in Radiological Workflows -- 2.7.5 Addressing Challenges in AI-Driven Radiology 2.8 Case Study: AI-Powered Detection of Pulmonary Diseases -- 2.9 Introduction to AI in Patient Monitoring -- 2.10 Case Study: AI for Enhanced Patient Monitoring and Care -- 2.11 Introduction to AI in Drug Discovery -- 2.11.1 AI's Impact on the Drug Discovery Process -- 2.11.2 The Role of AI in Personalized Medicine -- 2.11.3 Overcoming Challenges in Drug Discovery with AI -- 2.11.4 AI Collaborations in Pharma -- 2.12 Case Study: Accelerating Alzheimer's Drug Discovery -- 2.13 Ethical Debates and Perspectives in AI-Enhanced Healthcare -- 2.14 AI's Broad Impact Across Healthcare Sectors

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