Aligning Artificial Intelligence With Organizational Contexts Band 123 An Investigation Of Natural Language Processing In Clinical Healthcare

Aligning Artificial Intelligence with Organizational Contexts (Band 123) An Investigation of Natural Language Processing in Clinical Healthcare

Künstliche Intelligenz (KI) bietet enormes Potenzial, um Herausforderungen wie Fachkräftemangel und eine wachsende Zahl älterer Patientinnen und Patienten zu bewältigen. Gleichzeitig jedoch stellt die soziotechnische Einbettung von KI in Organisationen eine komplexe Aufgabe dar, deren Misslingen zu Wissensverlust oder Unzufriedenheit im Team führen kann. In dieser Dissertation werden die entscheidenden Komponenten dieses KI-Alignments systematisch untersucht. Vier Studien – davon zwei auf allgemeiner Ebene und zwei mit Fokus auf Natural Language Processing (NLP) im klinischen Bereich – beleuchten, wie KI und organisatorische Anforderungen bestmöglich aufeinander abgestimmt werden können. Dabei entsteht ein Rahmenwerk, das sowohl Forschenden als auch Praktikerinnen und Praktikern hilft, KI-Lösungen gezielt zu planen, zu integrieren und kontinuierlich zu verbessern. Zugleich eröffnet die Arbeit neue Perspektiven für Forschung und Anwendung, vor allem durch die Betrachtung von KI in spezifischen Kontexten und durch die gezielte Identifikation bisher unbeachteter Aspekte. Artificial Intelligence (AI) offers enormous potential for tackling challenges such as staffing shortages and a growing elderly population with increasing healthcare needs. However, effectively embedding AI in organizations is a complex sociotechnical endeavor; if misaligned, it can lead to knowledge loss or employee dissatisfaction. This dissertation systematically examines the key components of AI alignment. Four studies—two at a general level and two focused on Natural Language Processing (NLP) in clinical settings—explore how AI can best be harmonized with organizational requirements. The resulting framework supports researchers and practitioners alike in planning, integrating, and continuously refining AI solutions. Moreover, this work opens new horizons in research and practice by examining AI in specific contexts and identifying aspects that have received little attention thus far.

Aligning Artificial Intelligence with Organizational Contexts

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