Automation
• AI and Healthcare

References for Theme: AI and Healthcare

• Abel, Hendrik; Kleipaß, Ulrich
• "Moving the AI needle" (2020)

• Aquino, Yves Saint James; Rogers, Wendy A; Braunack-Mayer, Annette; Frazer, Helen; Win, Khin Than; Houssami, Nehmat; Degeling, Christopher; Semsarian, Christopher; Carter, Stacy M
• "Utopia versus dystopia: Professional perspectives on the impact of healthcare artificial intelligence on clinical roles and skills" (2023)

• Baik, Jaiwook
• "AI Techniques for Prognostics and Health Management" (2019)

• Blasimme, Alessandro; Vayena, Effy
• "The Ethics of AI in Biomedical Research, Patient Care, and Public Health" (2020)

• Bluemke, David A; Moy, Linda; Bredella, Miriam A; Ertl-Wagner, Birgit B; Fowler, Kathryn J; Goh, Vicky J; Halpern, Elkan F; Hess, Christopher P; Schiebler, Mark L; Weiss, Clifford R
• "Assessing Radiology Research on Artificial Intelligence: A Brief Guide for Authors, Reviewers, and Readers—From the Radiology Editorial Board" (2020)

  (p.488) Just like MRI or CT scanners, AI algorithms need independent validation. Commercial AI products may work in the computer laboratory but have poor function in the reading room.

• "Assessing Radiology Research on Artificial Intelligence: A Brief Guide for Authors, Reviewers, and Readers—From the Radiology Editorial Board" (2020)

  (p.489) Deep concern by radiologists about AI performance needs to be a major concern by our discipline as awhole.

• "Assessing Radiology Research on Artificial Intelligence: A Brief Guide for Authors, Reviewers, and Readers—From the Radiology Editorial Board" (2020)

• Chen, Irene Y; Szolovits, Peter; Ghassemi, Marzyeh
• "Can AI Help Reduce Disparities in General Medical and Mental Health Care?" (2019)

• Coeckelbergh, Mark
• "Health Care, Capabilities, and AI Assistive Technologies" (2010)

• "Health care, capabilities, and AI assistive technologies" (2010)

• Coghlan, Simon
• "Robots and the Possibility of Humanistic Care" (2021)

• Colonna, Liane
• "Artificial Intelligence in the Internet of Health Things: Is the Solution to AI Privacy More AI?" (n.d.)

• Ellahham, Samer; Ellahham, Nour; Simsekler, Mecit Can Emre
• "Application of Artificial Intelligence in the Health Care Safety Context: Opportunities and Challenges" (2019)

  (p.2) In health care, AI is defined as the mimicking of human cognitive functions by computers. AI has been inspiredby the functioning of biological neurons and includes the basics of sensing, recognition, and object recognition to enable machines to perform as good as or even better than humans. However, with the inherent lack of articulation and generation of insights, AI cannot replace physicians in health care.With no universally applicable rules in health care, AI must be supplemented with physician judgment in many instances. An extensive correlation of history and clinical findings is needed for the diagnosis or monitoring of any disease state. The physician–patient relationship is guided by associative and lateral thinking and can...

• "Application of Artificial Intelligence in the Health Care Safety Context: Opportunities and Challenges" (2019)

• Fiske, Amelia; Henningsen, Peter; Buyx, Alena
• "Your Robot Therapist Will See You Now: Ethical Implications of Embodied Artificial Intelligence in Psychiatry, Psychology, and Psychotherapy" (2019)

• Gasteiger, Norina; Broadbent, Elizabeth
• "AI, robotics, medicine and health sciences" (2021)

• Kalis, Brian; Collier, Matt; Fu, Richard
• "10 promising AI applications in health care" (2018)

• Lawry, Tom
• "The Road Ahead for AI" (2020)

• "When AI Meets HR" (2020)

• Maibaum, Arne; Bischof, Andreas; Hergesell, Jannis; Lipp, Benjamin
• "A critique of robotics in health care" (2021)

• Mina, Ashraf
• "Big data and artificial intelligence in future patient management. How is it all started? Where are we at now? And Quo Tendimus?" (2020)

  (p.5) Applying ML concept in computational pathology, which is defined as an approach to diagnosis that incorporates multiple sources of data (e. g. pathology, radiology, clinical, molecular and laboratory operations), presents clinically actionable knowledge to doctors, investigators and patients [31]. The work culture will play a significant role to be more inclusive to allow different experts from all relent areas to work cohesively together including, IT application specialists, medical and scientific experts, data scientists, hardware and software engineers, biostatisticians, and algorithm designers.

• "Big data and artificial intelligence in future patient management. How is it all started? Where are we at now? And Quo Tendimus?" (2020)

• Morley, Jessica; Floridi, Luciano
• "An ethically mindful approach to AI for health care" (2020)

• Morley, Jessica; Machado, Caio C V; Burr, Christopher; Cowls, Josh; Joshi, Indra; Taddeo, Mariarosaria; Floridi, Luciano
• "The ethics of AI in health care: A mapping review" (2020)

• "The ethics of AI in health care: A mapping review" (2020)

• Reddy, Sandeep; Allan, Sonia; Coghlan, Simon; Cooper, Paul
• "A governance model for the application of AI in health care" (2020)

• Saxena, Ankur; Brault, Nicolas; Rashid, Shazia
• Big Data and Artificial Intelligence for Healthcare Applications (2021)

• Seah, Jarrel C Y; Tang, Cyril H M; Buchlak, Quinlan D; Holt, Xavier G; Wardman, Jeffrey B; Aimoldin, Anuar; Esmaili, Nazanin; Ahmad, Hassan; Pham, Hung; Lambert, John F; Hachey, Ben; Hogg, Stephen J F; Johnston, Benjamin P; Bennett, Christine; Oakden-Rayner, Luke; Brotchie, Peter; Jones, Catherine M
• "Effect of a comprehensive deep-learning model on the accuracy of chest x-ray interpretation by radiologists: a retrospective, multireader multicase study" (2021)

• Shimonski, Robert
• AI in Healthcare: How Artificial Intelligence Is Changing IT Operations and Infrastructure Services (2021)

• Strickland, Eliza
• "IBM Watson, heal thyself: How IBM overpromised and underdelivered on AI health care" (2019)