Provider: NIHR Journals Library
Content:text/plain; charset="UTF-8"
TY  - JOUR
LB  - 1.
AU  - Gleeson, F
AU  - Revel, MP
AU  - Biederer, J
AU  - Larici, AR
AU  - Martini, K
AU  - Frauenfelder, T
TI  -  Implementation of artificial intelligence in thoracic imaging-a what, how, and why guide from the European Society of Thoracic Imaging (ESTI)
J2  - Eur Radiol
SP  - 5077
PY  - 2023
VL  - 33
SP  - 5077
ER  - 
TY  - ELEC
LB  - 2.
AU  - Harwich, E
AU  - Laycock, K
TI  -  Reform Research Trust
J2  - Thinking on Its Own: AI in the NHS
PY  - 2018
ER  - 
TY  - JOUR
LB  - 3.
AU  - Istasy, P
AU  - Lee, WS
AU  - Iansavichene, A
AU  - Upshur, R
AU  - Gyawali, B
AU  - Burkell, J
TI  -  The impact of artificial intelligence on health equity in oncology: scoping review
J2  - J Med Internet Res
SP  - e39748
PY  - 2022
VL  - 24
SP  - e39748
ER  - 
TY  - JOUR
LB  - 4.
AU  - Joy Mathew, C
AU  - David, AM
AU  - Joy Mathew, CM
TI  -  Artificial intelligence and its future potential in lung cancer screening
J2  - EXCLI J
SP  - 1552
PY  - 2020
VL  - 19
SP  - 1552
ER  - 
TY  - ELEC
LB  - 5.
AU  - National Institute for Health and Care Excellence
J2  - Artificial Intelligence-derived Software to Analyse Chest X-rays for Suspected Lung Cancer in Primary Care Referrals: Early Value Assessment
PY  - 2023
ER  - 
TY  - ELEC
LB  - 6.
AU  - NHS England
J2  - The NHS Long Term Plan
PY  - 2019
ER  - 
TY  - ELEC
LB  - 7.
AU  - NHS England
J2  - Artificial Intelligence (AI) and Machine Learning
PY  - 2023
ER  - 
TY  - ELEC
LB  - 8.
AU  - Darzi, A
J2  - Summary Letter from Lord Darzi to the Secretary of State for Health and Social Care
PY  - 2024
ER  - 
TY  - ELEC
LB  - 9.
AU  - NHS Confederation
J2  - AI in Healthcare: Navigating the Noise. A Comprehensive Guide Supporting Healthcare Leaders to Make Sense of AI and Explore the Art of the Possible
PY  - 2024
ER  - 
TY  - ELEC
LB  - 10.
AU  - NHS England
J2  - Integrated Health and Care
PY  - 2024
ER  - 
TY  - ELEC
LB  - 11.
AU  - Darzi, A
J2  - Investigation of the National Health Service in England
PY  - 2024
ER  - 
TY  - ELEC
LB  - 12.
AU  - Labour Party
J2  - Wes Streeting Speech at Labour Party Conference 2024
PY  - 2024
ER  - 
TY  - ELEC
LB  - 13.
AU  - NHS England
J2  - AI Deployment Platform
PY  - n.d
ER  - 
TY  - ELEC
LB  - 14.
AU  - NHS England
J2  - Artificial Intelligence in Health and Care Award
PY  - n.d
ER  - 
TY  - ELEC
LB  - 15.
AU  - The Royal College of Radiologists
J2  - Clinical Radiology Workforce Census
PY  - 2023
ER  - 
TY  - JOUR
LB  - 16.
AU  - Zhang, Z
AU  - Citardi, D
AU  - Wang, D
AU  - Genc, Y
AU  - Shan, J
AU  - Fan, X
TI  -  Patients’ perceptions of using artificial intelligence (AI)-based technology to comprehend radiology imaging data
J2  - Health Informatics J
SP  - 14604582211011215
PY  - 2021
VL  - 27
SP  - 14604582211011215
ER  - 
TY  - ELEC
LB  - 17.
AU  - National Institute for Health and Care Excellence
J2  - Artificial Intelligence (AI)-derived Software to Help Clinical Decision Making in Stroke
PY  - 2024
ER  - 
TY  - ELEC
LB  - 18.
AU  - National Institute for Health and Care Excellence
J2  - AI Technologies for Detecting Diabetic Retinopathy
PY  - 2021
ER  - 
TY  - JOUR
LB  - 19.
AU  - Liu, M
AU  - Wu, J
AU  - Wang, N
AU  - Zhang, X
AU  - Bai, Y
AU  - Guo, J
TI  -  The value of artificial intelligence in the diagnosis of lung cancer: a systematic review and meta-analysis
J2  - PLOS ONE
SP  - e0273445
PY  - 2023
VL  - 18
SP  - e0273445
ER  - 
TY  - JOUR
LB  - 20.
AU  - Chiu, HY
AU  - Chao, HS
AU  - Chen, YM
TI  -  Application of artificial intelligence in lung cancer
J2  - Cancers (Basel)
SP  - 1370
PY  - 2022
VL  - 14
SP  - 1370
ER  - 
TY  - JOUR
LB  - 21.
AU  - Fletcher, RR
AU  - Nakeshimana, A
AU  - Olubeko, O
TI  -  Addressing fairness, bias, and appropriate use of artificial intelligence and machine learning in global health
J2  - Front Artif Intell
SP  - 561802
PY  - 2020
VL  - 3
SP  - 561802
ER  - 
TY  - JOUR
LB  - 22.
AU  - Adams, SJ
AU  - Tang, R
AU  - Babyn, P
TI  -  Patient perspectives and priorities regarding artificial intelligence in radiology: opportunities for patient-centered radiology
J2  - J Am Coll Radiol
SP  - 1034
PY  - 2020
VL  - 17
SP  - 1034
ER  - 
TY  - JOUR
LB  - 23.
AU  - Fritsch, SJ
AU  - Blankenheim, A
AU  - Wahl, A
AU  - Hetfeld, P
AU  - Maassen, O
AU  - Deffge, S
TI  -  Attitudes and perception of artificial intelligence in healthcare: a cross-sectional survey among patients
J2  - Digit Health
PY  - 2022
VL  - 8
ER  - 
TY  - JOUR
LB  - 24.
AU  - Ibba, S
AU  - Tancredi, C
AU  - Fantesini, A
AU  - Cellina, M
AU  - Presta, R
AU  - Montanari, R
TI  -  How do patients perceive the AI-radiologists interaction? Results of a survey on 2119 responders
J2  - Eur J Radiol
SP  - 110917
PY  - 2023
VL  - 165
SP  - 110917
ER  - 
TY  - ELEC
LB  - 25.
AU  - NHS England
J2  - AI Diagnostic Fund
PY  - 2023
ER  - 
TY  - JOUR
LB  - 26.
AU  - Lawrence, R
AU  - Dodsworth, E
AU  - Massou, E
AU  - Sherlaw-Johnson, C
AU  - Ramsay, A
AU  - Walton, H
TI  -  Artificial Intelligence for diagnostics in radiology practice: a rapid systematic scoping review
J2  - EClinicalMedicine
SP  - 103228
PY  - 2025
VL  - 83
SP  - 103228
ER  - 
TY  - JOUR
LB  - 27.
AU  - Moher, D
AU  - Liberati, A
AU  - Tetzlaff, J
AU  - Altman, DG
AU  - Group, P
TI  -  Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement
J2  - PLOS Med
SP  - e1000097
PY  - 2009
VL  - 6
SP  - e1000097
ER  - 
TY  - JOUR
LB  - 28.
AU  - Greenhalgh, T
AU  - Wherton, J
AU  - Papoutsi, C
AU  - Lynch, J
AU  - Hughes, G
AU  - A’Court, C
TI  -  Beyond adoption: a new framework for theorizing and evaluating nonadoption, abandonment, and challenges to the scale-up, spread, and sustainability of health and care technologies
J2  - J Med Internet Res
SP  - e367
PY  - 2017
VL  - 19
SP  - e367
ER  - 
TY  - JOUR
LB  - 29.
AU  - Faric, N
AU  - Hinder, S
AU  - Williams, R
AU  - Ramaesh, R
AU  - Bernabeu, MO
AU  - van Beek, E
AU  - Cresswell, K
TI  -  Early experiences of integrating an artificial intelligence-based diagnostic decision support system into radiology settings: a qualitative study
J2  - Stud Health Technol Inform
SP  - 240
PY  - 2023
VL  - 309
SP  - 240
ER  - 
TY  - JOUR
LB  - 30.
AU  - Rainey, C
AU  - O’Regan, T
AU  - Matthew, J
AU  - Skelton, E
AU  - Woznitza, N
AU  - Chu, KY
TI  -  UK reporting radiographers’ perceptions of AI in radiographic image interpretation – current perspectives and future developments
J2  - Radiography (Lond)
SP  - 881
PY  - 2022
VL  - 28
SP  - 881
ER  - 
TY  - JOUR
LB  - 31.
AU  - Ng, CT
AU  - Roslan, SNA
AU  - Chng, YH
AU  - Choong, DAW
AU  - Chong, AJL
AU  - Tay, YX
TI  -  Singapore radiographers’ perceptions and expectations of artificial intelligence – a qualitative study
J2  - J Med Imaging Radiat Sci
SP  - 554
PY  - 2022
VL  - 53
SP  - 554
ER  - 
TY  - ELEC
LB  - 32.
AU  - Tricco, AC
AU  - Langlois, EV
AU  - Straus, SE
J2  - Rapid Reviews to Strengthen Health Policy Systems: A Practical Guide
PY  - 2017
ER  - 
TY  - ELEC
LB  - 33.
AU  - Popay, J
AU  - Roberts, H
AU  - Sowden, A
AU  - Petticrew, M
AU  - Arai, L
AU  - Rodgers, M
J2  - Guidance on the Conduct of Narrative Synthesis in Systematic Reviews: Lancaster University
PY  - 2006
ER  - 
TY  - JOUR
LB  - 34.
AU  - Braun, V
AU  - Clarke, V
TI  -  Using thematic analysis in psychology
J2  - Qual Res Psychol
SP  - 77
PY  - 2006
VL  - 3
SP  - 77
ER  - 
TY  - JOUR
LB  - 35.
AU  - Vindrola-Padros, C
AU  - Chisnall, G
AU  - Cooper, S
AU  - Dowrick, A
AU  - Djellouli, N
AU  - Symmons, SM
TI  -  Carrying out rapid qualitative research during a pandemic: emerging lessons from COVID-19
J2  - Qual Health Res
SP  - 2192
PY  - 2020
VL  - 30
SP  - 2192
ER  - 
TY  - ELEC
LB  - 36.
AU  - Roy Castle Lung Cancer Foundation Expert Group
J2  - National Optimal Lung Cancer Pathway (NOLCP) Version 4
PY  - 2024
ER  - 
TY  - JOUR
LB  - 37.
AU  - Strohm, L
AU  - Hehakaya, C
AU  - Ranschaert, ER
AU  - Boon, WPC
AU  - Moors, EHM
TI  -  Implementation of artificial intelligence (AI) applications in radiology: hindering and facilitating factors
J2  - Eur Radiol
SP  - 5525
PY  - 2020
VL  - 30
SP  - 5525
ER  - 
TY  - JOUR
LB  - 38.
AU  - Kim, B
AU  - Romeijn, S
AU  - van Buchem, M
AU  - Mehrizi, MHR
AU  - Grootjans, W
TI  -  A holistic approach to implementing artificial intelligence in radiology
J2  - Insights Imaging
SP  - 22
PY  - 2024
VL  - 15
SP  - 22
ER  - 
TY  - JOUR
LB  - 39.
AU  - Wenderott, K
AU  - Krups, J
AU  - Luetkens, JA
AU  - Weigl, M
TI  -  Radiologists’ perspectives on the workflow integration of an artificial intelligence-based computer-aided detection system: a qualitative study
J2  - Appl Ergon
SP  - 104243
PY  - 2024
VL  - 117
SP  - 104243
ER  - 
TY  - JOUR
LB  - 40.
AU  - Parmar, J
AU  - Sacrey, LA
AU  - Anderson, S
AU  - Charles, L
AU  - Dobbs, B
AU  - McGhan, G
TI  -  Facilitators, barriers and considerations for the implementation of healthcare innovation: a qualitative rapid systematic review
J2  - Health Soc Care Community
SP  - 856
PY  - 2022
VL  - 30
SP  - 856
ER  - 
TY  - JOUR
LB  - 41.
AU  - Santos, WJ
AU  - Graham, ID
AU  - Lalonde, M
AU  - Demery Varin, M
AU  - Squires, JE
TI  -  The effectiveness of champions in implementing innovations in health care: a systematic review
J2  - Implement Sci Commun
SP  - 80
PY  - 2022
VL  - 3
SP  - 80
ER  - 
TY  - JOUR
LB  - 42.
AU  - Syeed, MS
AU  - Poudel, N
AU  - Ngorsuraches, S
AU  - Veettil, SK
AU  - Chaiyakunapruk, N
TI  -  Characterizing attributes of innovation of technologies for healthcare: a systematic review
J2  - J Med Econ
SP  - 1158
PY  - 2022
VL  - 25
SP  - 1158
ER  - 
TY  - JOUR
LB  - 43.
AU  - Milella, F
AU  - Minelli, EA
AU  - Strozzi, F
AU  - Croce, D
TI  -  Change and innovation in healthcare: findings from literature
J2  - ClinicoEcon Outcomes Res
SP  - 395
PY  - 2021
VL  - 13
SP  - 395
ER  - 
TY  - JOUR
LB  - 44.
AU  - Shin, HD
AU  - Hamovitch, E
AU  - Gatov, E
AU  - MacKinnon, M
AU  - Samawi, L
AU  - Boateng, R
TI  -  The NASSS (Non-Adoption, Abandonment, Scale-Up, Spread and Sustainability) framework use over time: a scoping review
J2  - PLOS Digital Health
SP  - e0000418
PY  - 2025
VL  - 4
SP  - e0000418
ER  -