Intersections Of Law And Computational Intelligence In Health Governance
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Intersections of Law and Computational Intelligence in Health Governance
Intelligent technologies have vastly improved the efficiency of healthcare industries and intersections of law and governance. Computational intelligence provides effective tools for data management, contract analysis, legal research, and algorithm development. However, with the integration of computational intelligence in health governance, considerable legal concerns beg further exploration. Intersections of Law and Computational Intelligence in Health Governance examines computational intelligence related to healthcare and governance approaches. It addresses issues of healthcare data analysis and storage by presenting solutions using medical computational intelligence techniques. This book covers topics such as healthcare accessibility, medical law, deep learning, and drug discovery and classification, and is a valuable resource for lawyers, policy makers, healthcare workers, medical professionals, academicians, and researchers.
Machine Learning and Robotics in Urban Planning and Management
The integration of advanced technologies has led to drastic changes in the field of urban planning and management. When using large amounts of data from numerous sources, machine learning models can mimic past scenarios which predict future events. Urban planners use these predictions when making infrastructure or administrative decisions geared towards a highly efficient and sustainable urban environment. Machine learning algorithms can reduce the wait times at intersections, stop-and-go traffic, and overall congestion by adjusting signal timings on a real-time basis according to live density of vehicles. Conventional bottlenecks are identified and possible route changes proposed to generate improved traffic flow across regions. Further research may continue encouraging urban planning and management innovation. Machine Learning and Robotics in Urban Planning and Management explores the integration of machine learning and robotics technology in urban and regional development. It examines solutions for traffic management, infrastructure improvements, and prediction models using intelligent technology. This book covers topics such as neural networks, smart cities, and transportation systems, and is a useful resource for urban developers, business owners, scientists, civil engineers, academicians, and researchers.
Forensic Intelligence and Deep Learning Solutions in Crime Investigation
The massive advancement in various sectors of technology including forensic science is no exception. Integration of deep learning (DL) and artificial intelligence (AI) in forensic intelligence plays a vital role in the transformational shift in the effective approach towards the investigation of crimes and solving criminal investigations with foolproof evidence. As crimes grow increasingly sophisticated, traditional investigative tactics may be inadequate to grapple with the complexities of transnational criminal organizations. DL uses scientific tools for the recognition of patterns, image and speech analysis, and predictive modeling among others which are necessary to help solve crimes. By studying fingerprints, behavioral profiling, and DNA in digital forensics, AI powered tools provide observations that were inconceivable before now. Forensic Intelligence and Deep Learning Solutions in Crime Investigation discusses the numerous potential applications of deep learning and AI in forensic science. It explores how deep learning algorithms and AI technologies transform the role that forensic scientists and investigators play by enabling them to efficiently process and analyze vast amounts of data with very high accuracy in a short duration. Covering topics such as forensic ballistics, evidence processing, and crime scene analysis, this book is an excellent resource for forensic scientists, investigators, law enforcement, criminal justice professionals, computer scientists, legal professionals, policy makers, professionals, researchers, scholars, academicians, and more.