In this Handbook, distinguished experts in the field of administrative law discuss a wide range of issues from a comparative perspective. The book covers the historical beginnings of comparative administrative law scholarship, and discusses important methodological issues and basic concepts such as administrative power and accountability.

This collection of essays by leading academics, lawyers, parliamentarians and parliamentary officials provides a critical assessment of the UK Parliament's two main constitutional roles-as a legislature and as the preeminent institution for calling government to account. Both functions are undergoing change and facing new challenges. Part 1 (Legislation) includes chapters on Parliament's emerging responsibilities for pre-legislative scrutiny of government Bills and for evaluating proposed legislation against explicit constitutional standards. The impact on legislation of the European Union and the growing influence of the House of Lords are also examined. Part 2 (Accountability) investigates how Parliament operates to scrutinise areas of executive action previously often shielded from effective parliamentary oversight, including national security, war-making powers and administrative justice. There are also chapters on parliamentary reform, including analysis of the House of Commons 'Wright reforms', parliamentary sovereignty, privilege and the European Convention on Human Rights, Euroscepticism, and parliamentary sovereignty and the regulation of lobbyists. The book will be of interest to anyone who is curious about the work of Parliament and is aimed at legal academics, practitioners and political scientists.

Algorithms are a fundamental building block of artificial intelligence - and, increasingly, society - but our legal institutions have largely failed to recognize or respond to this reality. The Cambridge Handbook of the Law of Algorithms, which features contributions from US, EU, and Asian legal scholars, discusses the specific challenges algorithms pose not only to current law, but also - as algorithms replace people as decision makers - to the foundations of society itself. The work includes wide coverage of the law as it relates to algorithms, with chapters analyzing how human biases have crept into algorithmic decision-making about who receives housing or credit, the length of sentences for defendants convicted of crimes, and many other decisions that impact constitutionally protected groups. Other issues covered in the work include the impact of algorithms on the law of free speech, intellectual property, and commercial and human rights law.

The Model Rules of Professional Conduct provides an up-to-date resource for information on legal ethics. Federal, state and local courts in all jurisdictions look to the Rules for guidance in solving lawyer malpractice cases, disciplinary actions, disqualification issues, sanctions questions and much more. In this volume, black-letter Rules of Professional Conduct are followed by numbered Comments that explain each Rule's purpose and provide suggestions for its practical application. The Rules will help you identify proper conduct in a variety of given situations, review those instances where discretionary action is possible, and define the nature of the relationship between you and your clients, colleagues and the courts.

This open access book comprehensively covers the fundamentals of clinical data science, focusing on data collection, modelling and clinical applications. Topics covered in the first section on data collection include: data sources, data at scale (big data), data stewardship (FAIR data) and related privacy concerns. Aspects of predictive modelling using techniques such as classification, regression or clustering, and prediction model validation will be covered in the second section. The third section covers aspects of (mobile) clinical decision support systems, operational excellence and value-based healthcare. Fundamentals of Clinical Data Science is an essential resource for healthcare professionals and IT consultants intending to develop and refine their skills in personalized medicine, using solutions based on large datasets from electronic health records or telemonitoring programmes. The book’s promise is “no math, no code”and will explain the topics in a style that is optimized for a healthcare audience.