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AI Implementation in Radiology de Erik Ranschaert

AI Implementation in Radiology: Imaging Informatics for Healthcare Professionals

Editat de Erik Ranschaert, Mohammad H. Rezazade Mehrizi, Willem Grootjans, Tessa S. Cook
en Limba Engleză Paperback – 27 noi 2024

Remarcăm în AI Implementation in Radiology o abordare riguroasă a scenariilor clinice în care instituțiile medicale se confruntă cu dificultăți în adoptarea inteligenței artificiale. Volumul nu se limitează la prezentarea algoritmilor, ci analizează de ce multe implementări eșuează în practica de zi cu zi, oferind un cadru metodologic pentru transformarea procesului clinic. Reținem accentul pus pe managementul schimbării, esențial pentru a asigura o tranziție fără sincope și pentru a minimiza perturbările în fluxul de lucru radiologic.

Structura volumului reflectă o progresie logică, de la identificarea nevoii de schimbare și selecția soluțiilor AI adecvate, până la integrarea efectivă și instruirea personalului. Capitolele dedicate aspectelor legale și etice sunt fundamentale în contextul reglementărilor actuale, asigurând o desfășurare responsabilă a tehnologiei. Remarcăm, de asemenea, analiza impactului AI asupra raportării radiologice, un punct critic pentru eficiența operațională. Cuprinsul este organizat astfel încât să ghideze managerii de sănătate și radiologii prin toate etapele: planificare, implicarea părților interesate și evaluarea continuă a performanței.

Acesta este un manual de referință comparabil cu Artificial Intelligence in Medical Imaging, dar actualizat conform ghidurilor din 2024, punând un accent mult mai mare pe factorul uman și organizațional. Față de AI for Radiology de Oge Marques, care se concentrează pe analiza imaginilor medicale, lucrarea de față prioritizează „Translational Medicine” și pașii concreți necesari pentru ca AI să devină un instrument standardizat în spitalele moderne.

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Specificații

ISBN-13: 9783031689413
ISBN-10: 3031689410
Pagini: 192
Ilustrații: Approx. 180 p. 20 illus. in color.
Dimensiuni: 127 x 203 x 11 mm
Greutate: 0.24 kg
Ediția:2024
Editura: Springer
Colecția Imaging Informatics for Healthcare Professionals
Seria Imaging Informatics for Healthcare Professionals

Locul publicării:Cham, Switzerland

De ce să citești această carte

Recomandăm această carte liderilor din domeniul sănătății și medicilor radiologi care doresc să treacă de la faza experimentală a AI la utilizarea clinică de rutină. Cititorul câștigă o strategie clară de management al schimbării, învățând cum să navigheze barierele etice și tehnice. Este un ghid esențial pentru a optimiza diagnosticul și eficiența operațională într-un departament de imagistică modern.

Despre autor

Erik Ranschaert este un radiolog cu o vastă expertiză în informatică medicală, fiind unul dintre pionierii integrării AI în practica radiologică europeană. Împreună cu co-editorii Mohammad H. Rezazade Mehrizi, Willem Grootjans și Tessa S. Cook, acesta aduce o perspectivă multidisciplinară ce îmbină medicina clinică, știința datelor și managementul organizațional. Contribuțiile lor în seria Imaging Informatics for Healthcare Professionals sunt recunoscute pentru rigoarea academică și aplicabilitatea practică în transformarea digitală a radiologiei.

Descriere scurtă

This book describes change management in the context of implementing AI in medicine and radiology. Why do many medical institutions struggle to use AI in their clinical practice? What are the essential steps for and before an effective implementation of AI in radiology workflow? How can AI implementation trigger enduring improvements in the clinical process? The book shows how change management is crucial to effectively introduce AI to medicine and radiology, transform healthcare delivery and ensure a smooth transition while maximizing the benefits of AI and minimizing potential disruptions.
Change management in the context of AI in medicine and radiology involves a systematic approach to identify, plan, implement, and evaluate the integration of AI technologies into healthcare systems. It engages the necessary stakeholders at the appropriate points in the process to ensure that change is implemented properly. By effectively managing the change, healthcare organizations can harness the potential of AI to enhance patient care, improve diagnosis accuracy, and optimize operational efficiency in radiology and other medical specialties.
Throughout this change management process, organizations should prioritize ethical considerations, data privacy, and regulatory compliance to ensure that AI technologies are deployed responsibly and in accordance with relevant guidelines and regulations.

Cuprins

1 Introduction.- 2 Identification of the Need for Change.- 3 Planning and Goal Setting.- 4 Stakeholder Engagement and communication.- 5 Exploring and Assessing AI Solutions.- 6 Legal and ethical aspects of AI in radiology.- 7 Workflow Integration and Training.- 8 Evaluation, Monitoring, improvement.- 9 The impact of AI on radiology reporting.

Notă biografică

Dr. Erik Ranschaert is a radiologist at the St. Nikolaus Hospital in Eupen, Belgium, while also holding the position of visiting professor at Ghent University. With a strong focus on AI research, he collaborated with multiple institutions, including the Netherlands Cancer Institute, Tilburg University, VU Amsterdam, and Oxford University. During his tenure as President of the European Society of Medical Imaging Informatics (EuSoMII) from 2018 to 2021, Dr. Ranschaert spearheaded advancements in medical imaging technology. He continues to contribute as the chairman of the society's educational committee. Notably, his extensive portfolio includes several scientific publications, delving into the development and integration of AI applications in radiology. Dr. Ranschaert actively participated in various book projects, co-editing and co-authoring works on imaging informatics, including the pioneering book on AI in radiology. His expertise extends to advising hospitals, startups, and companies on the development and utilisation of AI for medical purposes, making him a respected authority in the field.
Mohammad H. Rezazade Mehrizi is an Associate Professor at KIN Center for Digital Innovation, at Vrije Universiteit Amsterdam. He is also an affiliated Organizational Learning Advisor to Leiden Medical Center, Radiology Department. He holds a PhD in Science and Technology Policy from Sharif University of Technology (in collaboration with SPRU), Iran, and a second PhD in Management Sciences from ESADE Business School, Barcelona. His interest lies in understanding and helping organizations and their associated communities to unlock their historical chains that prevent them from making a better future. He is research centers around how knowledge work and expertise are shaped by modern technologies, particularly by studying the effect of algorithmic technologies on professional work and organizing knowledge work. His scholarly work has contributed to numerous academic communities, and he has engaged with organizations and practitioners from various domains such as healthcare, digital technologies, financial services, and education.
Dr. Willem Grootjans is an assistant professor and technical physician at the department of Radiology at the Leiden University Medical Center. He graduated cum laude from the Technical University of Twente at the faculty of Science and Technology in Technical Medicine with a specialization in Robotics and Imaging. In 2012, he started his PhD at the department of Radiology and Nuclear Medicine of the Radboud University Medical Center in Nijmegen, focusing on the use of positron emission tomography for personalizing clinical management of patients with lung cancer. In 2016 he obtained his PhD at the Radboud faculty of Medical Sciences and started as a postdoctoral fellow at the Leiden University Medical Center at the department of Radiology. In 2018 he formed a specialized image processing group, at the department of Radiology of the Leiden University Medical Center, responsible for extracting relevant information from medical images for diagnosis and image-guided treatment decisions, also known as the ‘Imaging Services Group’ (ISG). Since 2019 he is head of the ISG which is now responsible for delivering high quality quantitative information to radiologists by using state-of-the art image processing software (including AI) that can be used for radiological reporting in clinical routine. Willem continues his mission to research and implement new technological innovations to improve the quality of healthcare, while keeping in mind the needs of the patient, healthcare professional, and society at the same time.
Dr. Tessa Cook is an Associate Professor of Radiology at the Perelman School of Medicine at the University of Pennsylvania in Philadelphia, and Vice Chair of Practice Transformation in the Department of Radiology. She is an active member of multiple radiology societies, including the RSNA, ACR, SIIM, and AUR. She is the director of the Penn Radiology Imaging Informatics Fellowship and Modality Chief of 3-D and Advanced Imaging. In 2020, Dr. Cook was inducted into the College of Fellows of the Society for Imaging Informatics in Medicine (SIIM) and received SIIM’s Dr. Ruth Dayhoff Award for the Advancement of Women in Medical Imaging Informatics. She was Chair of the SIIM Board of Directors from 2022-2024. Dr. Cook pursues innovative methods to enhance care delivery in radiology and improve radiologists' workflow.

Caracteristici

Identifies specific areas where AI has the potential to improve radiology workflow Helps with setting clear goals for implementing AI technologies and assessing their applicability Describes how implementing AI technologies for making the shift to sustainable radiology