scholarly journals Patients’ perceptions of using artificial intelligence (AI)-based technology to comprehend radiology imaging data

2021 ◽  
Vol 27 (2) ◽  
pp. 146045822110112
Author(s):  
Zhan Zhang ◽  
Daniel Citardi ◽  
Dakuo Wang ◽  
Yegin Genc ◽  
Juan Shan ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Thematic Analysis ◽  
Cyber Security ◽  
User Centered Design ◽  
Imaging Data ◽  
Imaging Studies ◽  
Structured Interviews ◽  
Patient Centered ◽  
Radiology Report ◽  
Radiology Reports

Results of radiology imaging studies are not typically comprehensible to patients. With the advances in artificial intelligence (AI) technology in recent years, it is expected that AI technology can aid patients’ understanding of radiology imaging data. The aim of this study is to understand patients’ perceptions and acceptance of using AI technology to interpret their radiology reports. We conducted semi-structured interviews with 13 participants to elicit reflections pertaining to the use of AI technology in radiology report interpretation. A thematic analysis approach was employed to analyze the interview data. Participants have a generally positive attitude toward using AI-based systems to comprehend their radiology reports. AI is perceived to be particularly useful in seeking actionable information, confirming the doctor’s opinions, and preparing for the consultation. However, we also found various concerns related to the use of AI in this context, such as cyber-security, accuracy, and lack of empathy. Our results highlight the necessity of providing AI explanations to promote people’s trust and acceptance of AI. Designers of patient-centered AI systems should employ user-centered design approaches to address patients’ concerns. Such systems should also be designed to promote trust and deliver concerning health results in an empathetic manner to optimize the user experience.

Artificial intelligence and the radiologist: the future in the Armed Forces Medical Services

2019 ◽  
pp. jramc-2018-001055
Author(s):  
Debraj Sen ◽  
R Chakrabarti ◽  
S Chatterjee ◽  
D S Grewal ◽  
K Manrai
Keyword(s):  
Artificial Intelligence ◽  
Information Technology ◽  
Cyber Security ◽  
Tertiary Care ◽  
Armed Forces ◽  
Medical Services ◽  
Imaging Biomarkers ◽  
Imaging Data ◽  
Adequate Funding ◽  
Trained Manpower

Artificial intelligence (AI) involves computational networks (neural networks) that simulate human intelligence. The incorporation of AI in radiology will help in dealing with the tedious, repetitive, time-consuming job of detecting relevant findings in diagnostic imaging and segmenting the detected images into smaller data. It would also help in identifying details that are oblivious to the human eye. AI will have an immense impact in populations with deficiency of radiologists and in screening programmes. By correlating imaging data from millions of patients and their clinico-demographic-therapy-morbidity-mortality profiles, AI could lead to identification of new imaging biomarkers. This would change therapy and direct new research. However, issues of standardisation, transparency, ethics, regulations, training, accreditation and safety are the challenges ahead. The Armed Forces Medical Services has widely dispersed units, medical echelons and roles ranging from small field units to large static tertiary care centres. They can incorporate AI-enabled radiological services to subserve small remotely located hospitals and detachments without posted radiologists and ease the load of radiologists in larger hospitals. Early widespread incorporation of information technology and enabled services in our hospitals, adequate funding, regular upgradation of software and hardware, dedicated trained manpower to manage the information technology services and train staff, and cyber security are issues that need to be addressed.

Recruitment Through AI in Selected Indian Companies

Metamorphosis ◽  
2022 ◽  
pp. 097262252110662
Author(s):  
Siddhi Mehrotra ◽  
Akanksha Khanna
Keyword(s):  
Artificial Intelligence ◽  
Human Resource ◽  
Thematic Analysis ◽  
Value Creation ◽  
Primary Sources ◽  
Structured Interviews ◽  
Business World ◽  
Technical Developments ◽  
Cost Cutting ◽  
Hr Managers

Artificial intelligence (AI) is being used very pervasively with the ever-evolving and competitive business world and has become the 21st-century buzzword. Countless innovations in technology have pushed businesses to make their value creation processes more effective and customer friendly. Digitization has played a significant role in reshaping the different human resource functions and processes. This study aims to elucidate the acceptance of automation in human resource management by employers and the degree to which recruiters can use AI to hire people. The study incorporates a thematic analysis approach, and the data is collected from primary sources by conducting semi-structured interviews with four experts working in IT organizations. This research would be useful for recruiters and HR managers to consider the fields of AI implementation and management to take advantage of cost-cutting technical developments.

scholarly journals Acceptability of artificial intelligence (AI)-led chatbot services in healthcare: A mixed-methods study

2019 ◽  
Vol 5 ◽  
pp. 205520761987180 ◽  
Author(s):  
Tom Nadarzynski ◽  
Oliver Miles ◽  
Aimee Cowie ◽  
Damien Ridge
Keyword(s):  
Artificial Intelligence ◽  
Cyber Security ◽  
Online Survey ◽  
Mixed Methods Study ◽  
Conversational Agents ◽  
Structured Interviews ◽  
Perceived Utility ◽  
Internet Users ◽  
It Skills ◽  
Engagement Intervention

Background Artificial intelligence (AI) is increasingly being used in healthcare. Here, AI-based chatbot systems can act as automated conversational agents, capable of promoting health, providing education, and potentially prompting behaviour change. Exploring the motivation to use health chatbots is required to predict uptake; however, few studies to date have explored their acceptability. This research aimed to explore participants’ willingness to engage with AI-led health chatbots. Methods The study incorporated semi-structured interviews (N-29) which informed the development of an online survey (N-216) advertised via social media. Interviews were recorded, transcribed verbatim and analysed thematically. A survey of 24 items explored demographic and attitudinal variables, including acceptability and perceived utility. The quantitative data were analysed using binary regressions with a single categorical predictor. Results Three broad themes: ‘Understanding of chatbots’, ‘AI hesitancy’ and ‘Motivations for health chatbots’ were identified, outlining concerns about accuracy, cyber-security, and the inability of AI-led services to empathise. The survey showed moderate acceptability (67%), correlated negatively with perceived poorer IT skills OR = 0.32 [CI95%:0.13–0.78] and dislike for talking to computers OR = 0.77 [CI95%:0.60–0.99] as well as positively correlated with perceived utility OR = 5.10 [CI95%:3.08–8.43], positive attitude OR = 2.71 [CI95%:1.77–4.16] and perceived trustworthiness OR = 1.92 [CI95%:1.13–3.25]. Conclusion Most internet users would be receptive to using health chatbots, although hesitancy regarding this technology is likely to compromise engagement. Intervention designers focusing on AI-led health chatbots need to employ user-centred and theory-based approaches addressing patients’ concerns and optimising user experience in order to achieve the best uptake and utilisation. Patients’ perspectives, motivation and capabilities need to be taken into account when developing and assessing the effectiveness of health chatbots.

scholarly journals Subspecialized Radiological Reporting Expedites Turnaround Time of Radiology Reports and Increases Productivity

2018 ◽  
Vol 190 (07) ◽  
pp. 623-629 ◽  
Author(s):  
Christoph Stern ◽  
Thomas Boehm ◽  
Burkhardt Seifert ◽  
Nadine Kawel-Boehm
Keyword(s):  
Turnaround Time ◽  
Radiology Department ◽  
Full Time ◽  
Imaging Studies ◽  
Radiology Report ◽  
Chi Square ◽  
Radiology Reports ◽  
Key Points ◽  
Chi Square Test ◽  
The Impact

Introduction To assess the impact of changing from general to subspecialized reporting on turnaround time of radiology reports (TAT), the fraction of radiology reports available within 24 hours (R< 24 h) and productivity. Materials and Methods Reporting workflow in our radiology department was changed from general reporting (radiologists report imaging studies of all areas [neuroradiological, abdominal, musculoskeletal imaging et cetera]) to subspecialized reporting (radiologists solely report imaging studies of their subspecialty field [e. g. musculoskeletal]). TAT, R< 24 h and productivity were calculated for a 12-month period of general reporting (January-December 2012) and compared to a 12-month period of subspecialized reporting (April 2014-March 2015) using Mann Whitney U-test, Pearson chi-square test and odds ratios, respectively. Results Report TAT decreased from a median of 17:04 hours (h) during general reporting to 3:38 h during subspecialized reporting, resulting in a 4.7-fold improvement (p < 0.001). R< 24 h improved significantly from 65 % to 87 % (p < 0.001). The odds of a radiology report being available < 24 h was 3.6- fold higher during subspecialized compared to general reporting. Productivity increased from a median of 301 to 376 (reports/full-time radiologist/month) (p = 0.001). Conclusion Changing the workflow from general to subspecialized reporting significantly improved the turnaround time of radiology reports, the fraction of radiology reports available within 24 hours and productivity. Key Points:  Citation Format

scholarly journals Radiologists in the loop: the roles of radiologists in the development of AI applications

2021 ◽  
Author(s):  
Damian Scheek ◽  
Mohammad. H. Rezazade Mehrizi ◽  
Erik Ranschaert
Keyword(s):  
Artificial Intelligence ◽  
Thematic Analysis ◽  
Development Process ◽  
Key Factors ◽  
Structured Interviews ◽  
Development Teams ◽  
Key Points ◽  
Wide Range ◽  
Quality Controller

Abstract Objectives To examine the various roles of radiologists in different steps of developing artificial intelligence (AI) applications. Materials and methods Through the case study of eight companies active in developing AI applications for radiology, in different regions (Europe, Asia, and North America), we conducted 17 semi-structured interviews and collected data from documents. Based on systematic thematic analysis, we identified various roles of radiologists. We describe how each role happens across the companies and what factors impact how and when these roles emerge. Results We identified 9 roles that radiologists play in different steps of developing AI applications: (1) problem finder (in 4 companies); (2) problem shaper (in 3 companies); (3) problem dominator (in 1 company); (4) data researcher (in 2 companies); (5) data labeler (in 3 companies); (6) data quality controller (in 2 companies); (7) algorithm shaper (in 3 companies); (8) algorithm tester (in 6 companies); and (9) AI researcher (in 1 company). Conclusions Radiologists can play a wide range of roles in the development of AI applications. How actively they are engaged and the way they are interacting with the development teams significantly vary across the cases. Radiologists need to become proactive in engaging in the development process and embrace new roles. Key Points • Radiologists can play a wide range of roles during the development of AI applications. • Both radiologists and developers need to be open to new roles and ways of interacting during the development process. • The availability of resources, time, expertise, and trust are key factors that impact how actively radiologists play roles in the development process.

scholarly journals Creating patient-centered radiology reports to empower patients undergoing prostate magnetic resonance imaging

2020 ◽  
Vol 15 (4) ◽  
Author(s):  
Nathan Perlis ◽  
Antonio Finelli ◽  
Mike Lovas ◽  
Alejandro Berlin ◽  
Janet Papadakos ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Decision Making ◽  
Magnetic Resonance ◽  
Human Factors Engineering ◽  
Resonance Imaging ◽  
Structured Interviews ◽  
Mri Findings ◽  
Patient Centered ◽  
Prostate Mri ◽  
Radiology Reports

Introduction: As we progress to an era when patient autonomy and shared decision-making are highly valued, there is a need to also have effective patient-centered communication tools. Radiology reports are designed for clinicians and can be very technical and difficult for patients to understand. It is important for patients to understand their magnetic resonance imaging (MRI) report in order to make an informed treatment decision with their physician. Therefore, we aimed to create a patient-centered prostate MRI report in order to give our patients a better understanding of their clinical condition. Methods: A prototype patient-centered radiology report (PACERR) was created by identifying items to include based on opinions sought from a group of patients undergoing prostate MRI and medical experts. Data was collected in semi-structured interviews using a salient belief question. A prototype PACERR was created in collaboration with human factors engineering and design, medical imaging, biomedical informatics, and cancer patient education groups. Results: Fifteen patients and eight experts from urology, radiation oncology, radiology, and nursing participated in this study. Patients were particularly interested to have a report with laymen terms, concise language, contextualization of values, definitions of medical terms, and next course of action. Everyone believed the report should include the risk of MRI findings actually being cancer in the subsequent biopsy. Conclusions: A prostate MRI PACERR has been developed to communicate the most important findings relevant to decision-making in prostate cancer using patient-oriented design principles. The ability of this tool to improve patient knowledge and communication will be explored.

MO1044DESIGN OF THERAPEUTIC EDUCATION WORKSHOPS FOR HOME HEAMODIALYSIS IN A PATIENT-CENTERED CKD RESEARCH: A QUALITATIVE STUDY

2021 ◽  
Vol 36 (Supplement_1) ◽  
Author(s):  
Abdallah Guerraoui ◽  
Roula Galland ◽  
Flora Belkahla-Delabruyere ◽  
Odile Didier ◽  
Pierre Sauvajon ◽  
...  
Keyword(s):  
Family Environment ◽  
Thematic Analysis ◽  
Therapeutic Education ◽  
Structured Interviews ◽  
Patient Centered ◽  
Home Dialysis ◽  
Team Members ◽  
Home Haemodialysis ◽  
Education Workshop ◽  
The Impact

Abstract Background and Aims A quarter of the patients did not receive any information on any modality before the start of Renal Remplacement Therapy (RRT). We have therapeutic education workshops for all RRT except for home haemodialysis (HHD). We aimed to identify and describe the needs of patients and caregivers for RRT with HHD. Lastly, to conceive and carry out a Therapeutic Education Workshop. Method Two sequential methods of qualitative data collection were undertaken: (1) interviews with a patient who had been on HHD and a doctor specialized in HHD. (2) semi-structured interviews with HHD patients in our center. Analytic Approach Thematic analysis. We used thematic analysis and systematically coded and identified themes inductively from data. To ensure that the range and depth of data were reflected in the analysis, transcripts were independently analyzed by 2 research team members experienced in qualitative research. Transcribed interviews were entered into RQDA 3.6.1 (2019-07-05) software for data organization and coding purposes (Version 3.6.1). Patient interviews were ceased when no new codes were identified (data saturation) after five consecutive interviews. Results We identified six themes related to the barriers, facilitators, and potential solutions to home dialysis therapy: (1) HHD allows autonomy and freedom with constraints, (2) safety of the care environment, (3) the caregiver and family environment, (4) patient’s experience and experiential knowledge, (5) self-treatment experience - Impact on life, and (6) factors that impact the choice of treatment with HHD. we designed a model for a therapeutic education workshop in a group of 4 patients and 4 caregivers. Our approach is the person-centered model of care. The workshop is composed of 4 educational sequences Conclusion Our study confirmed previous results obtained about the major barriers, facilitators, and potential solutions to HHD. There are three important points regarding HHD: (1) the impact of the HHD on the caregiver, (2) the experience of patients already treated with HHD, and (3) the role of nurses and nephrologists in informing and educating. A program to develop patient-to-patient peer mentorship, allowing patients to discuss their dialysis experience, would be invaluable.

‘Are we on the same wavelength?’ International nurses and the process of confronting and adjusting to clinical communication in Australia

2017 ◽  
Vol 13 (3) ◽  
pp. 263-274 ◽  
Author(s):  
Tonia Crawford ◽  
Peter Roger ◽  
Sally Candlin
Keyword(s):  
Communication Skills ◽  
Thematic Analysis ◽  
Care Setting ◽  
Linguistically Diverse ◽  
The Other ◽  
Culturally And Linguistically Diverse ◽  
Central Theme ◽  
Structured Interviews ◽  
Clinical Communication ◽  
Professional Experiences

Effective communication skills are important in the health care setting in order to develop rapport and trust with patients, provide reassurance, assess patients effectively and provide education in a way that patients easily understand (Candlin and Candlin, 2003). However with many nurses from culturally and linguistically diverse (CALD) backgrounds being recruited to fill the workforce shortfall in Australia, communication across cultures with the potential for miscommunication and ensuing risks to patient safety has gained increasing focus in recent years (Shakya and Horsefall, 2000; Chiang and Crickmore, 2009). This paper reports on the first phase of a study that examines intercultural nurse patient communication from the perspective of four Registered Nurses from CALD backgrounds working in Australia. Five interrelating themes that were derived from thematic analysis of semi-structured interviews are discussed. The central theme of ‘adjustment’ was identified as fundamental to the experiences of the RNs and this theme interrelated with each of the other themes that emerged: professional experiences with communication, ways of showing respect, displaying empathy, and vulnerability.

Reports of the Workshops Held at the 2019 AAAI Conference on Artificial Intelligence

AI Magazine ◽  
2019 ◽  
Vol 40 (3) ◽  
pp. 67-78
Author(s):  
Guy Barash ◽  
Mauricio Castillo-Effen ◽  
Niyati Chhaya ◽  
Peter Clark ◽  
Huáscar Espinoza ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Language Processing ◽  
Cyber Security ◽  
Question Answering ◽  
Intent Recognition ◽  
Affective Content ◽  
Learning Plan ◽  
Dialog System ◽  
Affective Content Analysis ◽  
Games And Simulations

The workshop program of the Association for the Advancement of Artificial Intelligence’s 33rd Conference on Artificial Intelligence (AAAI-19) was held in Honolulu, Hawaii, on Sunday and Monday, January 27–28, 2019. There were fifteen workshops in the program: Affective Content Analysis: Modeling Affect-in-Action, Agile Robotics for Industrial Automation Competition, Artificial Intelligence for Cyber Security, Artificial Intelligence Safety, Dialog System Technology Challenge, Engineering Dependable and Secure Machine Learning Systems, Games and Simulations for Artificial Intelligence, Health Intelligence, Knowledge Extraction from Games, Network Interpretability for Deep Learning, Plan, Activity, and Intent Recognition, Reasoning and Learning for Human-Machine Dialogues, Reasoning for Complex Question Answering, Recommender Systems Meet Natural Language Processing, Reinforcement Learning in Games, and Reproducible AI. This report contains brief summaries of the all the workshops that were held.

A Survey on Artificial Intelligence Techniques to Prevent Cyber Crime

2018 ◽  
Vol 8 (5) ◽  
pp. 80
Author(s):  
Juveriya Afreen
Keyword(s):  
Artificial Intelligence ◽  
Cyber Security ◽  
Data Security ◽  
Human Reasoning ◽  
Cyber Crime ◽  
Artificial Intelligence Techniques

Abstract-- With increase in complexity of data, security, it is difficult for the individuals to prevent the offence. Thus, by using any automation or software it’s not possible by only using huge fixed algorithms to overcome this. Thus, we need to look for something which is robust and feasible enough. Hence AI plays an epitome role to defense such violations. In this paper we basically look how human reasoning along with AI can be applied to uplift cyber security.

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