Chapter 14 Advancing healthcare through the opportunities and challenges of quantum computing
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Amena Mahmoud
Abstract
Quantum computing can revolutionize healthcare by solving complex problems that ordinary computers cannot. This chapter discusses the pros and cons of quantum computing in healthcare. Drug R&D offers a great possibility. Quantum computers can correctly model molecular interactions and chemical processes, making it easier to search enormous chemical spaces for drug candidates. This could speed up drug discovery and produce more effective and targeted treatments. Quantum computing has great potential in personalized medicine. Quantum algorithms allow healthcare providers to evaluate genomic data and find complex genetic patterns. This helps personalize healthcare by creating medicines and preventive measures according to each person’s genetic profile. However, quantum computing in healthcare has challenges. The high cost and limited accessibility of quantum technologies hinder its widespread application. The complexity and expertise required to construct and operate quantum systems also hinder their widespread adoption. Despite these challenges, quantum computing in healthcare has clear benefits. With technology improving, the healthcare business must explore and invest in quantum computing. The industry will uncover novel illness prevention, diagnostic, and treatment options, improving patient outcomes and creating a stronger, fairer healthcare system.
Abstract
Quantum computing can revolutionize healthcare by solving complex problems that ordinary computers cannot. This chapter discusses the pros and cons of quantum computing in healthcare. Drug R&D offers a great possibility. Quantum computers can correctly model molecular interactions and chemical processes, making it easier to search enormous chemical spaces for drug candidates. This could speed up drug discovery and produce more effective and targeted treatments. Quantum computing has great potential in personalized medicine. Quantum algorithms allow healthcare providers to evaluate genomic data and find complex genetic patterns. This helps personalize healthcare by creating medicines and preventive measures according to each person’s genetic profile. However, quantum computing in healthcare has challenges. The high cost and limited accessibility of quantum technologies hinder its widespread application. The complexity and expertise required to construct and operate quantum systems also hinder their widespread adoption. Despite these challenges, quantum computing in healthcare has clear benefits. With technology improving, the healthcare business must explore and invest in quantum computing. The industry will uncover novel illness prevention, diagnostic, and treatment options, improving patient outcomes and creating a stronger, fairer healthcare system.
Chapters in this book
- Frontmatter I
- Contents V
- List of contributors VII
- Chapter 1 Quantum computing in society: impacts and implications 1
- Chapter 2 Quantum computing with machine learning: opportunities and challenges 19
- Chapter 3 Quantum machine learning algorithms: a comprehensive review 37
- Chapter 4 Highlighting major issues with quantum computing in healthcare 53
- Chapter 5 Privacy and security for 6G’s IoT-connected future in the age of quantum computing 67
- Chapter 6 Can quantum computers revolutionize health systems? 87
- Chapter 7 Industrial automation and quantum computing 105
- Chapter 8 Applications of quantum computing in financial planning and financial control 127
- Chapter 9 Quantum computing in machine learning: an overview 141
- Chapter 10 The impact of AI and automation on income inequality in BRICS countries and the role of structural factors and women’s empowerment 155
- Chapter 11 Quantum computing and machine learning: a symbiotic relationship 177
- Chapter 12 Quantum-secured healthcare data and cybersecurity innovations in the era of Industry 5.0 199
- Chapter 13 Introduction to quantum computing and its revolution in industry and society 219
- Chapter 14 Advancing healthcare through the opportunities and challenges of quantum computing 239
- Chapter 15 Quantum computing in drug and chemical 255
- Index 279
Chapters in this book
- Frontmatter I
- Contents V
- List of contributors VII
- Chapter 1 Quantum computing in society: impacts and implications 1
- Chapter 2 Quantum computing with machine learning: opportunities and challenges 19
- Chapter 3 Quantum machine learning algorithms: a comprehensive review 37
- Chapter 4 Highlighting major issues with quantum computing in healthcare 53
- Chapter 5 Privacy and security for 6G’s IoT-connected future in the age of quantum computing 67
- Chapter 6 Can quantum computers revolutionize health systems? 87
- Chapter 7 Industrial automation and quantum computing 105
- Chapter 8 Applications of quantum computing in financial planning and financial control 127
- Chapter 9 Quantum computing in machine learning: an overview 141
- Chapter 10 The impact of AI and automation on income inequality in BRICS countries and the role of structural factors and women’s empowerment 155
- Chapter 11 Quantum computing and machine learning: a symbiotic relationship 177
- Chapter 12 Quantum-secured healthcare data and cybersecurity innovations in the era of Industry 5.0 199
- Chapter 13 Introduction to quantum computing and its revolution in industry and society 219
- Chapter 14 Advancing healthcare through the opportunities and challenges of quantum computing 239
- Chapter 15 Quantum computing in drug and chemical 255
- Index 279
