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Pham C, Poorzargar K, Panesar D, Lee K, Wong J, Parotto M, Chung F. Video plethysmography for contactless blood pressure and heart rate measurement in perioperative care. J Clin Monit Comput 2024; 38:121-130. [PMID: 37715858 DOI: 10.1007/s10877-023-01074-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2023] [Accepted: 08/30/2023] [Indexed: 09/18/2023]
Abstract
The purpose of this study was to evaluate the feasibility and accuracy of remote Video Plethysmography (VPPG) for contactless measurements of blood pressure (BP) and heart rate (HR) in adult surgical patients in a hospital setting. An iPad Pro was used to record a 1.5-minute facial video of the participant's face and VPPG was used to extract vital signs measurements. A standard medical device (Welch Allyn) was used for comparison to measure BP and HR. Trial registration: NCT05165381. Two-hundred-sixteen participants consented and completed the contactless BP and HR monitoring (mean age 54.1 ± 16.8 years, 58% male). The consent rate was 75% and VPPG was 99% successful in capturing BP and HR. VPPG predicted SBP, DBP, and HR with a measurement bias ± SD, -8.18 ± 16.44 mmHg, - 6.65 ± 9.59 mmHg, 0.09 ± 6.47 beats/min respectively. Pearson's correlation for all measurements between VPPG and standard medical device was significant. Correlation for SBP was moderate (0.48), DBP was weak (0.29), and HR was strong (0.85). Most patients were satisfied with the non-contact technology with an average rating of 8.7/10 and would recommend it for clinical use. VPPG was highly accurate in measuring HR, and is currently not accurate in measuring BP in surgical patients. The VPPG BP algorithm showed limitations in capturing individual variations in blood pressure, highlighting the need for further improvements to render it clinically effective across all ranges. Contactless vital signs monitoring was well-received and earned a high satisfaction score.
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Affiliation(s)
- Chi Pham
- Department of Anesthesia and Pain Medicine, Toronto Western Hospital, University Health Network, University of Toronto, Toronto, ON, Canada
- Institute of Medical Science, Faculty of Medicine, University of Toronto, Toronto, ON, Canada
| | - Khashayar Poorzargar
- Department of Anesthesia and Pain Medicine, Toronto Western Hospital, University Health Network, University of Toronto, Toronto, ON, Canada
- Institute of Medical Science, Faculty of Medicine, University of Toronto, Toronto, ON, Canada
| | - Darshan Panesar
- Ontario Institute for Studies in Education, University of Toronto, Toronto, ON, Canada
| | - Kang Lee
- Ontario Institute for Studies in Education, University of Toronto, Toronto, ON, Canada
| | - Jean Wong
- Department of Anesthesia and Pain Medicine, Toronto Western Hospital, University Health Network, University of Toronto, Toronto, ON, Canada
- Institute of Medical Science, Faculty of Medicine, University of Toronto, Toronto, ON, Canada
| | - Matteo Parotto
- Department of Anesthesia and Pain Medicine, Toronto General Hospital, University Health Network, University of Toronto, Toronto, ON, Canada
| | - Frances Chung
- Department of Anesthesia and Pain Medicine, Toronto Western Hospital, University Health Network, University of Toronto, Toronto, ON, Canada.
- Institute of Medical Science, Faculty of Medicine, University of Toronto, Toronto, ON, Canada.
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Jenkinson GP, Houghton N, van Zalk N, Waller J, Bello F, Tzemanaki A. Acceptability of Automated Robotic Clinical Breast Examination: Survey Study. J Particip Med 2023; 15:e42704. [PMID: 37010907 PMCID: PMC10131668 DOI: 10.2196/42704] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2022] [Revised: 01/14/2023] [Accepted: 02/20/2023] [Indexed: 02/22/2023] Open
Abstract
BACKGROUND In the United Kingdom, women aged 50 to 70 years are invited to undergo mammography. However, 10% of invasive breast cancers occur in women aged ≤45 years, representing an unmet need for young women. Identifying a suitable screening modality for this population is challenging; mammography is insufficiently sensitive, whereas alternative diagnostic methods are invasive or costly. Robotic clinical breast examination (R-CBE)-using soft robotic technology and machine learning for fully automated clinical breast examination-is a theoretically promising screening modality with early prototypes under development. Understanding the perspectives of potential users and partnering with patients in the design process from the outset is essential for ensuring the patient-centered design and implementation of this technology. OBJECTIVE This study investigated the attitudes and perspectives of women regarding the use of soft robotics and intelligent systems in breast cancer screening. It aimed to determine whether such technology is theoretically acceptable to potential users and identify aspects of the technology and implementation system that are priorities for patients, allowing these to be integrated into technology design. METHODS This study used a mixed methods design. We conducted a 30-minute web-based survey with 155 women in the United Kingdom. The survey comprised an overview of the proposed concept followed by 5 open-ended questions and 17 closed questions. Respondents were recruited through a web-based survey linked to the Cancer Research United Kingdom patient involvement opportunities web page and distributed through research networks' mailing lists. Qualitative data generated via the open-ended questions were analyzed using thematic analysis. Quantitative data were analyzed using 2-sample Kolmogorov-Smirnov tests, 1-tailed t tests, and Pearson coefficients. RESULTS Most respondents (143/155, 92.3%) indicated that they would definitely or probably use R-CBE, with 82.6% (128/155) willing to be examined for up to 15 minutes. The most popular location for R-CBE was at a primary care setting, whereas the most accepted method for receiving the results was an on-screen display (with an option to print information) immediately after the examination. Thematic analysis of free-text responses identified the following 7 themes: women perceive that R-CBE has the potential to address limitations in current screening services; R-CBE may facilitate increased user choice and autonomy; ethical motivations for supporting R-CBE development; accuracy (and users' perceptions of accuracy) is essential; results management with clear communication is a priority for users; device usability is important; and integration with health services is key. CONCLUSIONS There is a high potential for the acceptance of R-CBE in its target user group and a high concordance between user expectations and technological feasibility. Early patient participation in the design process allowed the authors to identify key development priorities for ensuring that this new technology meets the needs of users. Ongoing patient and public involvement at each development stage is essential.
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Affiliation(s)
- George P Jenkinson
- Bristol Robotics Laboratory, Department of Mechanical Engineering, University of Bristol, Bristol, United Kingdom
| | - Natasha Houghton
- Centre for Engagement and Simulation Science, Department of Surgery and Cancer, Imperial College London, London, United Kingdom
| | - Nejra van Zalk
- Dyson School of Design Engineering, Imperial College London, London, United Kingdom
| | - Jo Waller
- Cancer Prevention Group, School of Cancer & Pharmaceutical Sciences, King's College London, London, United Kingdom
| | - Fernando Bello
- Centre for Engagement and Simulation Science, Department of Surgery and Cancer, Imperial College London, London, United Kingdom
| | - Antonia Tzemanaki
- Bristol Robotics Laboratory, Department of Mechanical Engineering, University of Bristol, Bristol, United Kingdom
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González Aguña A, Gonzalo de Diego B, Páez Ramos S, Fernández Batalla M, Jiménez Rodríguez ML, Santamaría García JM. Care Robotics: An Assessment of Professional Perception in the Face of the COVID-19 Pandemic. Healthcare (Basel) 2023; 11:healthcare11070946. [PMID: 37046875 PMCID: PMC10094221 DOI: 10.3390/healthcare11070946] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2022] [Revised: 03/15/2023] [Accepted: 03/21/2023] [Indexed: 03/29/2023] Open
Abstract
The COVID-19 crisis accelerated the adoption of technologies. Technological advancement is also expected in robotics applied to any sector, including in healthcare. The aim is to assess the professional perception of care robotics facing COVID-19. This study aimed to (1) select a tool for assessing different aspects of healthcare, (2) analyse the professional perception about the development, usefulness and helpfulness of technologies and robotics in the field of healthcare and (3) evaluate the correlation between the perceived helpfulness of care robotics and the selected tool. We implement five validated clinical tests which integrate 80 items about a person and their clinical situation. From the sample of 46 professionals, 95.65% affirmed that technology was moderately to completely useful for professional performance in the context of the pandemic, lowering to 67.39% when asked only about robotics; 93.48% stated that the inclusion of robotics in at least one health area affected by COVID-19 would have helped them. Finally, the variables extracted from clinical tests corresponded to the most relevant health areas as identified by the professionals. This research shows the potential of care robotics oriented towards healthcare from a care paradigm.
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Affiliation(s)
- Alexandra González Aguña
- Henares University Hospital, Community of Madrid Health Service (SERMAS), 28822 Madrid, Spain
- Research Group MISKC, Department of Computer Science, University of Alcala, Polytechnic Building, University Campus, Barcelona Road Km. 33.6, 28805 Alcalá de Henares, Spain; (B.G.d.D.); (S.P.R.); (M.F.B.); (M.L.J.R.); (J.M.S.G.)
- Correspondence:
| | - Blanca Gonzalo de Diego
- Research Group MISKC, Department of Computer Science, University of Alcala, Polytechnic Building, University Campus, Barcelona Road Km. 33.6, 28805 Alcalá de Henares, Spain; (B.G.d.D.); (S.P.R.); (M.F.B.); (M.L.J.R.); (J.M.S.G.)
- Meco Health Centre, Community of Madrid Health Service (SERMAS), 28880 Madrid, Spain
| | - Sandra Páez Ramos
- Research Group MISKC, Department of Computer Science, University of Alcala, Polytechnic Building, University Campus, Barcelona Road Km. 33.6, 28805 Alcalá de Henares, Spain; (B.G.d.D.); (S.P.R.); (M.F.B.); (M.L.J.R.); (J.M.S.G.)
- Meco Health Centre, Community of Madrid Health Service (SERMAS), 28880 Madrid, Spain
| | - Marta Fernández Batalla
- Research Group MISKC, Department of Computer Science, University of Alcala, Polytechnic Building, University Campus, Barcelona Road Km. 33.6, 28805 Alcalá de Henares, Spain; (B.G.d.D.); (S.P.R.); (M.F.B.); (M.L.J.R.); (J.M.S.G.)
| | - María Lourdes Jiménez Rodríguez
- Research Group MISKC, Department of Computer Science, University of Alcala, Polytechnic Building, University Campus, Barcelona Road Km. 33.6, 28805 Alcalá de Henares, Spain; (B.G.d.D.); (S.P.R.); (M.F.B.); (M.L.J.R.); (J.M.S.G.)
- Computer Science Department, University of Alcala, 28805 Madrid, Spain
| | - José María Santamaría García
- Research Group MISKC, Department of Computer Science, University of Alcala, Polytechnic Building, University Campus, Barcelona Road Km. 33.6, 28805 Alcalá de Henares, Spain; (B.G.d.D.); (S.P.R.); (M.F.B.); (M.L.J.R.); (J.M.S.G.)
- Meco Health Centre, Community of Madrid Health Service (SERMAS), 28880 Madrid, Spain
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Farzandipour M, Nabovati E, Sharif R. The effectiveness of tele-triage during the COVID-19 pandemic: A systematic review and narrative synthesis. J Telemed Telecare 2023:1357633X221150278. [PMID: 36683438 PMCID: PMC9892819 DOI: 10.1177/1357633x221150278] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2022] [Accepted: 12/21/2022] [Indexed: 01/24/2023]
Abstract
BACKGROUND Telehealth services were used by healthcare centers during the COVID-19 pandemic in order to identify and manage patients at the forefront of the healthcare system. As one of these technologies, tele-triage refers to the assessment of a patient's health status through telephone or another means of communication and recommending treatment or providing appropriate referrals in emergency rooms and primary care offices. This study aimed to perform a systematic review of the evidence on the effectiveness of tele-triage, as one of these technologies, during the COVID-19 pandemic. METHODS Medline (via PubMed), Scopus, and Web of Science databases were searched for relevant English articles published since the pandemic's onset until December 30, 2021. Studies investigating the tele-triage's effect on patient safety, clinical outcomes, and patient satisfaction were included. Data on study characteristics, intervention characteristics, and their effects on study outcomes were extracted separately by two authors. A narrative synthesis of the included studies was ultimately performed. RESULTS Out of the 6312 retrieved studies, 14 met the inclusion criteria. The tele-triage intervention was offered by an algorithm-based system in eight studies (57.14%) and by healthcare providers in six other studies (42.86%) to determine the patient's level of care. According to the results, tele-triage interventions during COVID-19 can reduce unnecessary emergency room visits (by 1.2-22.2%), improve clinical outcomes after intervention (such as would closure in diabetic feet), reduce mortality and injuries, and ensure patient satisfaction with tele-triage (53-98%). CONCLUSIONS This study found that tele-triage interventions reduced unnecessary visits, improved clinical outcomes, reduced mortality, and injuries, increased patient satisfaction, reduced healthcare provider workload, improved access to primary care consultation, and increased patient safety and satisfaction. Therefore, tele-triage systems are not only suitable for providing acute and emergency care remotely but they are also recommended as an alternative tool to monitor and diagnose COVID-19.
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Affiliation(s)
- Mehrdad Farzandipour
- Health Information Management Research Center, Department of Health Information Management & Technology, School of Allied Health Professions, Kashan University of Medical Sciences, Kashan, Iran
| | - Ehsan Nabovati
- Health Information Management Research Center, Department of Health Information Management & Technology, School of Allied Health Professions, Kashan University of Medical Sciences, Kashan, Iran
| | - Reihane Sharif
- Health Information Management Research Center, Department of Health Information Management & Technology, School of Allied Health Professions, Kashan University of Medical Sciences, Kashan, Iran
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Singh G, DeWalle J, Tanriover B, Singh N, Chang AR, Anand PM. Effect of age and rural residency on perceptions about SARS-CoV-2 pandemic and vaccination in kidney transplant recipients. Transpl Infect Dis 2022; 24:e13943. [PMID: 36169231 PMCID: PMC9539214 DOI: 10.1111/tid.13943] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2022] [Revised: 06/09/2022] [Accepted: 07/04/2022] [Indexed: 12/24/2022]
Abstract
BACKGROUND Transplant patients have poor outcomes in coronavirus-disease 2019 (COVID-19). The pandemic's effects on rural patients' overall care experience, attitudes to telemedicine, and vaccination are poorly understood. METHODS We administered a cross-sectional survey to adult kidney transplant recipients in central Pennsylvania across four clinical sites between March 29, 2021 and June 2, 2021. We assessed the pandemic's impact on care access, telemedicine experience, attitudes toward preventive measures, vaccination, and variation by sociodemographic variables. RESULTS Survey completion rate was 51% (303/594). Of these, 52.8% were rural residents. The most common impact was use of telemedicine (79.2%). Predominant barriers to telemedicine were lack of video devices (10.9%), perceived complexity (5.6%), and technical issues (5.3%). On a 0-10 Likert scale, the mean positive impression for telemedicine was 7.7; lower for patients with telephone-only versus video visits (7.0 vs. 8.2; p < .001), and age ≥60 years (7.4 vs. 8.1; p = .01) on univariate analyses. Time/travel savings were commonly identified (115/241, 47.7%) best parts of telemedicine and lack of personal connection (70/166, 42.2%) the worst. Only 68.9% had received any dose of COVID vaccination. The vaccinated group members were older (58.4 vs. 53.5 years; p = .007), and less likely rural (47.8% vs. 65.2%; p = .005). Common themes associated with vaccine hesitancy included concerns about safety (27/59, 46%), perceived lack of data (19/59, 32%), and distrust (17/59, 29%). At least one misconception about the vaccines or COVID-19 was quoted by 29% of vaccine-hesitant patients. CONCLUSIONS Among respondents, the pandemic significantly impacted healthcare experience, especially in older patients in underserved communities. COVID-19 vaccination rate was relatively low, driven by misconceptions and lack of trust.
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Affiliation(s)
- Gurmukteshwar Singh
- Department of NephrologyGeisinger HealthDanvillePennsylvaniaUSA,Kidney Health Research InstituteGeisinger HealthDanvillePennsylvaniaUSA
| | - Joseph DeWalle
- Department of Population Health SciencesGeisinger HealthDanvillePennsylvaniaUSA
| | - Bekir Tanriover
- Division of NephrologyUniversity of Arizona College of MedicineTusconArizonaUSA
| | - Neeraj Singh
- John C. McDonald Regional Transplant CenterLouisiana State UniversityShreveportLouisianaUSA
| | - Alex R. Chang
- Department of NephrologyGeisinger HealthDanvillePennsylvaniaUSA,Kidney Health Research InstituteGeisinger HealthDanvillePennsylvaniaUSA
| | - Prince M. Anand
- Division of NephrologyMedical University of South CarolinaCharlestonSouth CarolinaUSA
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Huang HW, Chen J, Chai PR, Ehmke C, Rupp P, Dadabhoy FZ, Feng A, Li C, Thomas AJ, da Silva M, Boyer EW, Traverso G. Mobile Robotic Platform for Contactless Vital Sign Monitoring. Cyborg and Bionic Systems 2022; 2022. [DOI: 10.34133/2022/9780497] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022] Open
Abstract
The COVID-19 pandemic has accelerated methods to facilitate contactless evaluation of patients in hospital settings. By minimizing in-person contact with individuals who may have COVID-19, healthcare workers can prevent disease transmission and conserve personal protective equipment. Obtaining vital signs is a ubiquitous task that is commonly done in person by healthcare workers. To eliminate the need for in-person contact for vital sign measurement in the hospital setting, we developed Dr. Spot, a mobile quadruped robotic system. The system includes IR and RGB cameras for vital sign monitoring and a tablet computer for face-to-face medical interviewing. Dr. Spot is teleoperated by trained clinical staff to simultaneously measure the skin temperature, respiratory rate, and heart rate while maintaining social distancing from patients and without removing their mask. To enable accurate, contactless measurements on a mobile system without a static black body as reference, we propose novel methods for skin temperature compensation and respiratory rate measurement at various distances between the subject and the cameras, up to 5 m. Without compensation, the skin temperature MAE is 1.3°C. Using the proposed compensation method, the skin temperature MAE is reduced to 0.3°C. The respiratory rate method can provide continuous monitoring with a MAE of 1.6 BPM in 30 s or rapid screening with a MAE of 2.1 BPM in 10 s. For the heart rate estimation, our system is able to achieve a MAE less than 8 BPM in 10 s measured in arbitrary indoor light conditions at any distance below 2 m.
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Affiliation(s)
- Hen-Wei Huang
- Department of Mechanical Engineering, Massachusetts Institute of Technology, USA
- The Koch Institute of Integrated Cancer Research, Massachusetts Institute of Technology, USA
- Division of Gastroenterology, Brigham and Women’s Hospital, Harvard Medical School, USA
| | - Jack Chen
- Division of Gastroenterology, Brigham and Women’s Hospital, Harvard Medical School, USA
- Department of Engineering Science, University of Toronto, Canada
| | - Peter R. Chai
- The Koch Institute of Integrated Cancer Research, Massachusetts Institute of Technology, USA
- Department of Emergency Medicine, Brigham and Women’s Hospital, Harvard Medical School, USA
- Department of Psychosocial Oncology and Palliative Care, Dana Farber Cancer Institute, USA
- The Fenway Institute, USA
| | - Claas Ehmke
- The Koch Institute of Integrated Cancer Research, Massachusetts Institute of Technology, USA
| | - Philipp Rupp
- Division of Gastroenterology, Brigham and Women’s Hospital, Harvard Medical School, USA
| | - Farah Z. Dadabhoy
- Department of Emergency Medicine, Brigham and Women’s Hospital, Harvard Medical School, USA
| | - Annie Feng
- The Koch Institute of Integrated Cancer Research, Massachusetts Institute of Technology, USA
| | - Canchen Li
- The Koch Institute of Integrated Cancer Research, Massachusetts Institute of Technology, USA
| | - Akhil J. Thomas
- The Koch Institute of Integrated Cancer Research, Massachusetts Institute of Technology, USA
| | | | - Edward W. Boyer
- Department of Emergency Medicine, Brigham and Women’s Hospital, Harvard Medical School, USA
- The Fenway Institute, USA
| | - Giovanni Traverso
- Department of Mechanical Engineering, Massachusetts Institute of Technology, USA
- Division of Gastroenterology, Brigham and Women’s Hospital, Harvard Medical School, USA
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Huang HW, Rupp P, Chen J, Kemkar A, Khandelwal N, Ballinger I, Chai P, Traverso G. Cost-Effective Solution of Remote Photoplethysmography Capable of Real-Time, Multi-Subject Monitoring with Social Distancing. Proc IEEE Sens 2022; 2022:10.1109/sensors52175.2022.9967120. [PMID: 36570065 PMCID: PMC9788727 DOI: 10.1109/sensors52175.2022.9967120] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Recent advances in remote-photoplethysmography (rPPG) have enabled the measurement of heart rate (HR), oxygen saturation (SpO2), and blood pressure (BP) in a fully contactless manner. These techniques are increasingly applied clinically given a desire to minimize exposure to individuals with infectious symptoms. However, accurate rPPG estimation often leads to heavy loading in computation that either limits its real-time capacity or results in a costly setup. Additionally, acquiring rPPG while maintaining protective distance would require high resolution cameras to ensure adequate pixels coverage for the region of interest, increasing computational burden. Here, we propose a cost-effective platform capable of the real-time, continuous, multi-subject monitoring while maintaining social distancing. The platform is composed of a centralized computing unit and multiple low-cost wireless cameras. We demonstrate that the central computing unit is able to simultaneously handle continuous rPPG monitoring of five subjects with social distancing without compromising the frame rate and rPPG accuracy.
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Affiliation(s)
- Hen-Wei Huang
- Division of Gastroenterology, Brigham & Women’s Hospital, Harvard Medical School, Boston, MA 02115 USA,The Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02142 USA,Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139 USA
| | - Philip Rupp
- Division of Gastroenterology, Brigham & Women’s Hospital, Harvard Medical School, Boston, MA 02115 USA
| | - Jack Chen
- Division of Gastroenterology, Brigham & Women’s Hospital, Harvard Medical School, Boston, MA 02115 USA
| | - Abhijay Kemkar
- Division of Gastroenterology, Brigham & Women’s Hospital, Harvard Medical School, Boston, MA 02115 USA
| | - Naitik Khandelwal
- Division of Gastroenterology, Brigham & Women’s Hospital, Harvard Medical School, Boston, MA 02115 USA
| | - Ian Ballinger
- Division of Gastroenterology, Brigham & Women’s Hospital, Harvard Medical School, Boston, MA 02115 USA
| | - Peter Chai
- The Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02142 USA,Department of Emergency Medicine, Brigham & Women’s Hospital, Harvard Medical School, Boston, MA 02115 USA
| | - Giovanni Traverso
- Division of Gastroenterology, Brigham & Women’s Hospital, Harvard Medical School, Boston, MA 02115 USA,The Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02142 USA,Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139 USA
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Malamateniou C, Knapp KM, Pergola M, Woznitza N, Hardy M. Artificial intelligence in radiography: Where are we now and what does the future hold? Radiography (Lond) 2021; 27 Suppl 1:S58-S62. [PMID: 34380589 DOI: 10.1016/j.radi.2021.07.015] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2021] [Revised: 07/10/2021] [Accepted: 07/21/2021] [Indexed: 10/20/2022]
Abstract
OBJECTIVES This paper will outline the status and basic principles of artificial intelligence (AI) in radiography along with some thoughts and suggestions on what the future might hold. While the authors are not always able to separate the current status from future developments in this field, given the speed of innovation in AI, every effort has been made to give a view to the present with projections to the future. KEY FINDINGS AI is increasingly being integrated within radiography and radiographers will increasingly be working with AI based tools in the future. As new AI tools are developed it is essential that robust validation is undertaken in unseen data, supported by more prospective interdisciplinary research. A framework of stronger, more comprehensive approvals are recommended and the involvement of service users, including practitioners, patients and their carers in the design and implementation of AI tools is essential. Clearer accountability and medicolegal frameworks are required in cases of erroneous results from the use of AI-powered software and hardware. Clearer career pathways and role extension provision for healthcare practitioners, including radiographers, are required along with education in this field where AI will be central. CONCLUSION With the current growth rate of AI tools it is expected that many of the applications in medical imaging will continue to develop to more accurate, less expensive and more readily available versions moving from the bench to the bedside. The hope is that, alongside efficiency and increased patient throughput, patient centred care and precision medicine will find their way in, so we will not only deliver a faster, safer, seamless clinical service but also one that will have the patients at its heart. IMPACT FOR PRACTICE AI is already reaching clinical practice in many forms and its presence will continue to increase over the short and long-term future. Radiographers must learn to work with AI, embracing it and maximising the positive outcomes from this new technology.
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Affiliation(s)
| | | | - M Pergola
- American Society of Radiologic Technologists, NM, USA.
| | - N Woznitza
- University College London Hospitals, UK; Canterbury Christ Church University, UK
| | - M Hardy
- University of Bradford, Bradford, UK
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