1.

Record Nr.

UNINA9910483211303321

Titolo

Algorithmic Governance and Governance of Algorithms : Legal and Ethical Challenges / / edited by Martin Ebers, Marta Cantero Gamito

Pubbl/distr/stampa

Cham : , : Springer International Publishing : , : Imprint : Springer, , 2021

ISBN

3-030-50559-6

Edizione

[1st ed. 2021.]

Descrizione fisica

1 online resource (IX, 167 p. 3 illus., 1 illus. in color.)

Collana

Data Science, Machine Intelligence, and Law, , 2730-5902 ; ; 1

Disciplina

343.0999

Soggetti

Information technology - Law and legislation

Mass media - Law and legislation

Machine learning

Robotics

IT Law, Media Law, Intellectual Property

Machine Learning

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Nota di contenuto

Algorithmic Governance and Governance of Algorithms: An Introduction -- Privacy, Non-Discrimination and Equal Treatment: Developing a Fundamental Rights Response to Behavioural Profiling -- The Black Box on Trial: The Impact of Algorithmic Opacity on Fair Trial Rights in Criminal Proceedings -- Microchipping Employees: Unlawful Monitoring Practice or a New Trend in the Workplace? -- Electronic Personhood: A Tertium Genus for Smart Autonomous Surgical Robots? -- Online Behavioural Advertising and Unfair Manipulation Between the GDPR and the UCPD -- Protecting Deep Learning: Could the New EU-Trade Secrets Directive Be an Option for the Legal Protection of Artificial Neural Networks? -- Chinese Copyright Law and Computer-Generated Works in the Era of Artificial Intelligence.

Sommario/riassunto

Algorithms are now widely employed to make decisions that have increasingly far-reaching impacts on individuals and society as a whole (“algorithmic governance”), which could potentially lead to manipulation, biases, censorship, social discrimination, violations of privacy, property rights, and more. This has sparked a global debate on



how to regulate AI and robotics (“governance of algorithms”). This book discusses both of these key aspects: the impact of algorithms, and the possibilities for future regulation.

2.

Record Nr.

UNINA9911034861803321

Autore

Salvatori Marcus

Titolo

Anesthesia for Lung Transplant / / edited by Marcus Salvatori, Alexander Huang

Pubbl/distr/stampa

Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2025

ISBN

3-032-06112-1

Edizione

[1st ed. 2025.]

Descrizione fisica

1 online resource (217 pages)

Collana

Medicine Series

Altri autori (Persone)

HuangAlexander

Disciplina

617.96

Soggetti

Anesthesiology

Transplantation of organs, tissues, etc

Critical care medicine

Respiratory organs

Physiology

Transplantation

Intensive Care Medicine

Respiratory Physiology

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Nota di contenuto

DONORS AND PROCUREMENT -- EX VIVO LUNG PERFUSION -- RECIPIENTS -- PERIOPERATIVE PLANNING AND MONITORS -- INDUCTION -- AIRWAY MANAGEMENT -- CENTRAL LINES -- ANESTHESIA AND ANALGESIA -- TRANSPLANT SEQUENCE -- VENTILATION -- HEMODYNAMICS AND ECMO -- REPERFUSION -- PRIMARY GRAFT DYSFUNCTION -- FLUIDS AND METABOLICS -- COAGULATION AND TRANSFUSION -- TRANSFER TO ICU -- SPECIAL SITUATIONS.

Sommario/riassunto

This book originates from Toronto General Hospital (TGH), one of the largest and most experienced lung transplant center in the world, which to date has completed over 3000 lung transplant procedures,



and currently averages 200 procedures per year. The book captures the full perioperative scope of lung transplantation, including preoperative, intraoperative, and postoperative management. It is written in a “Frequently Asked Question” (FAQ) style and addresses issues and questions encountered during lung transplantation procedures, providing rationale from both clinical experience and published literature wherever possible. Anesthesia for Lung Transplant fills the need for a practical guide offering anesthesiologists, surgeons, respirologists and intensivists new to the field with actionable advice.