Role Of Artificial Intelligence In Advancing Applied Life Sciences

The Role of Artificial Intelligence in Advancing Applied Life Sciences

The transformative role of artificial intelligence (AI) is revolutionizing the life sciences sector. AI is being used to accelerate drug discovery, personalize treatments, and improve patient outcomes. AI has demonstrated its potential in optimizing crop yields, enhancing food safety, and addressing global food security challenges. Additionally, AI has applications in climate modeling, species conservation, and pollution monitoring. Discussion of AI implementation in life sciences may stimulate further research and development in AI-driven life science solutions. The Role of Artificial Intelligence in Advancing Applied Life Sciences equips readers with a solid understanding of technology's potential to address complex life science problems. It also discusses the ethical implications and challenges associated with AI implementation in this field. Covering topics such as biomanufacturing, disease identification, and climate change patters, this book is an excellent resource for life scientists, computer scientists, healthcare practitioners, environmentalists, agriculturalists, professionals, researchers, scholars, academicians, and more.

The Role of Artificial Intelligence in Advancing Applied Life Sciences

Artificial Intelligence in Healthcare

Artificial Intelligence (AI) in Healthcare is more than a comprehensive introduction to artificial intelligence as a tool in the generation and analysis of healthcare data. The book is split into two sections where the first section describes the current healthcare challenges and the rise of AI in this arena. The ten following chapters are written by specialists in each area, covering the whole healthcare ecosystem. First, the AI applications in drug design and drug development are presented followed by its applications in the field of cancer diagnostics, treatment and medical imaging. Subsequently, the application of AI in medical devices and surgery are covered as well as remote patient monitoring. Finally, the book dives into the topics of security, privacy, information sharing, health insurances and legal aspects of AI in healthcare. - Highlights different data techniques in healthcare data analysis, including machine learning and data mining - Illustrates different applications and challenges across the design, implementation and management of intelligent systems and healthcare data networks - Includes applications and case studies across all areas of AI in healthcare data