scholarly journals PEACE: Perception and Expectations toward Artificial Intelligence in Capsule Endoscopy

2021 ◽  
Vol 10 (23) ◽  
pp. 5708
Author(s):  
Romain Leenhardt ◽  
Ignacio Fernandez-Urien Sainz ◽  
Emanuele Rondonotti ◽  
Ervin Toth ◽  
Cedric Van de Bruaene ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Capsule Endoscopy ◽  
Online Survey ◽  
Reading Time ◽  
General Information ◽  
Care Group ◽  
Complete Replacement ◽  
National Leaders ◽  
The Mean ◽  
Standardize Reporting

Artificial intelligence (AI) has shown promising results in digestive endoscopy, especially in capsule endoscopy (CE). However, some physicians still have some difficulties and fear the advent of this technology. We aimed to evaluate the perceptions and current sentiments toward the use of AI in CE. An online survey questionnaire was sent to an audience of gastroenterologists. In addition, several European national leaders of the International CApsule endoscopy REsearch (I CARE) Group were asked to disseminate an online survey among their national communities of CE readers (CER). The survey included 32 questions regarding general information, perceptions of AI, and its use in daily life, medicine, endoscopy, and CE. Among 380 European gastroenterologists who answered this survey, 333 (88%) were CERs. The mean average time length of experience in CE reading was 9.9 years (0.5–22). A majority of CERs agreed that AI would positively impact CE, shorten CE reading time, and help standardize reporting in CE and characterize lesions seen in CE. Nevertheless, in the foreseeable future, a majority of CERs disagreed with the complete replacement all CE reading by AI. Most CERs believed in the high potential of AI for becoming a valuable tool for automated diagnosis and for shortening the reading time. Currently, the perception is that AI will not replace CE reading.

scholarly journals Role of Artificial Intelligence in Video Capsule Endoscopy

Diagnostics ◽  
2021 ◽  
Vol 11 (7) ◽  
pp. 1192
Author(s):  
Ioannis Tziortziotis ◽  
Faidon-Marios Laskaratos ◽  
Sergio Coda
Keyword(s):  
Artificial Intelligence ◽  
Small Bowel ◽  
Capsule Endoscopy ◽  
Performance Metrics ◽  
General Information ◽  
Widespread Application ◽  
Promising Tool ◽  
Open Questions ◽  
Bowel Cleansing

Capsule endoscopy (CE) has been increasingly utilised in recent years as a minimally invasive tool to investigate the whole gastrointestinal (GI) tract and a range of capsules are currently available for evaluation of upper GI, small bowel, and lower GI pathology. Although CE is undoubtedly an invaluable test for the investigation of small bowel pathology, it presents considerable challenges and limitations, such as long and laborious reading times, risk of missing lesions, lack of bowel cleansing score and lack of locomotion. Artificial intelligence (AI) seems to be a promising tool that may help improve the performance metrics of CE, and consequently translate to better patient care. In the last decade, significant progress has been made to apply AI in the field of endoscopy, including CE. Although it is certain that AI will find soon its place in day-to-day endoscopy clinical practice, there are still some open questions and barriers limiting its widespread application. In this review, we provide some general information about AI, and outline recent advances in AI and CE, issues around implementation of AI in medical practice and potential future applications of AI-aided CE.

scholarly journals Artificial Intelligence in Capsule Endoscopy: A Practical Guide to Its Past and Future Challenges

Diagnostics ◽  
2021 ◽  
Vol 11 (9) ◽  
pp. 1722
Author(s):  
Sang Hoon Kim ◽  
Yun Jeong Lim
Keyword(s):  
Artificial Intelligence ◽  
Capsule Endoscopy ◽  
Reading Time ◽  
Diagnostic Process ◽  
The Past ◽  
Computer Aided ◽  
Future Challenges ◽  
Medical Diagnostic ◽  
Reading System ◽  
Near Future

Artificial intelligence (AI) has revolutionized the medical diagnostic process of various diseases. Since the manual reading of capsule endoscopy videos is a time-intensive, error-prone process, computerized algorithms have been introduced to automate this process. Over the past decade, the evolution of convolutional neural network (CNN) enabled AI to detect multiple lesions simultaneously with increasing accuracy and sensitivity. Difficulty in validating CNN performance and unique characteristics of capsule endoscopy images make computer-aided reading systems in capsule endoscopy still on a preclinical level. Although AI technology can be used as an auxiliary second observer in capsule endoscopy, it is expected that in the near future, it will effectively reduce the reading time and ultimately become an independent, integrated reading system.

scholarly journals Multicenter prospective evaluation of the express view reading mode for small-bowel capsule endoscopy studies

2018 ◽  
Vol 06 (05) ◽  
pp. E616-E621 ◽  
Author(s):  
Jean-Christophe Saurin ◽  
Philippe Jacob ◽  
Laurent Heyries ◽  
Christian Pesanti ◽  
Franck Cholet ◽  
...  
Keyword(s):  
Small Bowel ◽  
Capsule Endoscopy ◽  
Reading Time ◽  
High Sensitivity ◽  
Prospective Evaluation ◽  
Precise Location ◽  
The Mean ◽  
Film Reading ◽  
Consensus Reading ◽  
Significant Lesion

Abstract Background Reducing the reading time of capsule endoscopy films is of high priority for gastroenterologists. We report a prospective multicenter evaluation of an “express view” reading mode (Intromedic capsule system). Methods Eighty-three patients with obscure gastrointestinal bleeding were prospectively included in 10 centers. All patients underwent small-bowel capsule endoscopy (Intromedic, Seoul, Republic of Korea). Films were read in standard mode, then a second reading was performed in express view mode at a second center. For each lesion, the precise location, nature, and relevance were collected. A consensus reading and review were done by three experts, and considered to be the gold standard. Results The mean reading time of capsule films was 39.7 minutes (11 – 180 minutes) and 19.7 minutes (4 – 40 minutes) by standard and express view mode, respectively (P < 1 × 10 – 4). The consensus review identified a significant lesion in 44/83 patients (53.0 %). Standard reading and express view reading had a 93.3 % and 82.2 % sensitivity, respectively (NS). Consensus review identified 70 significant images from which standard reading and express view reading detected 58 (82.9 %) and 55 (78.6 %), respectively. The informatics algorithm detected 66/70 images (94.3 %) thus missing four small-bowel angiodysplasia. Conclusion The express view algorithm allows an important shortening of Intromedic capsule film reading time with a high sensitivity.

THE NEW GENERATION OF EXPRESS VIEW IS HIGHLY ACCURATE AND IS EFFECTIVE TO REDUCE CAPSULE ENDOSCOPY READING TIME

2020 ◽  
Author(s):  
S Piccirelli ◽  
A Mussetto ◽  
A Bellumat ◽  
R Cannizzaro ◽  
M Pennazio ◽  
...  
Keyword(s):  
Capsule Endoscopy ◽  
Reading Time ◽  
New Generation

Attitudes of Medical Workers Toward Artificial Intelligence in Ophthalmology: A Comparative Survey (Preprint)

2020 ◽  
Author(s):  
Weihua Yang ◽  
Bo Zheng ◽  
Maonian Wu ◽  
Shaojun Zhu ◽  
Hongxia Zhou ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Medical Ethics ◽  
Online Survey ◽  
Medical Professionals ◽  
Medical Field ◽  
Acceptance Level ◽  
Professional Workers ◽  
Basic Understanding ◽  
Comparative Survey ◽  
Definition Of

BACKGROUND Artificial intelligence (AI) is widely applied in the medical field, especially in ophthalmology. In the development of ophthalmic artificial intelligence, some problems worthy of attention have gradually emerged, among which the ophthalmic AI-related recognition issues are particularly prominent. That is to say, currently, there is a lack of research into people's familiarity with and their attitudes toward ophthalmic AI. OBJECTIVE This survey aims to assess medical workers’ and other professional technicians’ familiarity with AI, as well as their attitudes toward and concerns of ophthalmic AI. METHODS An electronic questionnaire was designed through the Questionnaire Star APP, an online survey software and questionnaire tool, and was sent to relevant professional workers through Wechat, China’s version of Facebook or WhatsApp. The participation was based on a voluntary and anonymous principle. The questionnaire mainly consisted of four parts, namely the participant’s background, the participant's basic understanding of AI, the participant's attitude toward AI, and the participant's concerns about AI. A total of 562 participants were counted, with 562 valid questionnaires returned. The results of the questionnaires are displayed in an Excel 2003 form. RESULTS A total of 562 professional workers completed the questionnaire, of whom 291 were medical workers and 271 were other professional technicians. About 37.9% of the participants understood AI, and 31.67% understood ophthalmic AI. The percentages of people who understood ophthalmic AI among medical workers and other professional technicians were about 42.61% and 15.6%, respectively. About 66.01% of the participants thought that ophthalmic AI would partly replace doctors, with about 59.07% still having a relatively high acceptance level of ophthalmic AI. Meanwhile, among those with ophthalmic AI application experiences (30.6%), respectively about 84.25% of medical professionals and 73.33% of other professional technicians held a full acceptance attitude toward ophthalmic AI. The participants expressed concerns that ophthalmic AI might bring about issues such as the unclear definition of medical responsibilities, the difficulty of ensuring service quality, and the medical ethics risks. And among the medical workers and other professional technicians who understood ophthalmic AI, 98.39%, and 95.24%, respectively, said that there was a need to increase the study of medical ethics issues in the ophthalmic AI field. CONCLUSIONS Analysis of the questionnaire results shows that the medical workers have a higher understanding level of ophthalmic AI than other professional technicians, making it necessary to popularize ophthalmic AI education among other professional technicians. Most of the participants did not have any experience in ophthalmic AI, but generally had a relatively high acceptance level of ophthalmic AI, believing that doctors would partly be replaced by it and that there was a need to strengthen research into medical ethics issues of the field.

scholarly journals A survey of clinicians on the use of artificial intelligence in ophthalmology, dermatology, radiology and radiation oncology

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jane Scheetz ◽  
Philip Rothschild ◽  
Myra McGuinness ◽  
Xavier Hadoux ◽  
H. Peter Soyer ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
New Zealand ◽  
Radiation Oncology ◽  
Online Survey ◽  
New Technology ◽  
Medical Liability ◽  
Healthcare Outcomes ◽  
Medical Workforce ◽  
Artificial Intelligence Technology ◽  
Workforce Needs

AbstractArtificial intelligence technology has advanced rapidly in recent years and has the potential to improve healthcare outcomes. However, technology uptake will be largely driven by clinicians, and there is a paucity of data regarding the attitude that clinicians have to this new technology. In June–August 2019 we conducted an online survey of fellows and trainees of three specialty colleges (ophthalmology, radiology/radiation oncology, dermatology) in Australia and New Zealand on artificial intelligence. There were 632 complete responses (n = 305, 230, and 97, respectively), equating to a response rate of 20.4%, 5.1%, and 13.2% for the above colleges, respectively. The majority (n = 449, 71.0%) believed artificial intelligence would improve their field of medicine, and that medical workforce needs would be impacted by the technology within the next decade (n = 542, 85.8%). Improved disease screening and streamlining of monotonous tasks were identified as key benefits of artificial intelligence. The divestment of healthcare to technology companies and medical liability implications were the greatest concerns. Education was identified as a priority to prepare clinicians for the implementation of artificial intelligence in healthcare. This survey highlights parallels between the perceptions of different clinician groups in Australia and New Zealand about artificial intelligence in medicine. Artificial intelligence was recognized as valuable technology that will have wide-ranging impacts on healthcare.

scholarly journals Respiratory Telerehabilitation of Boys and Young Men with Duchenne Muscular Dystrophy in the COVID-19 Pandemic

2021 ◽  
Vol 18 (12) ◽  
pp. 6179
Author(s):  
Agnieszka Sobierajska-Rek ◽  
Łukasz Mański ◽  
Joanna Jabłońska-Brudło ◽  
Karolina Śledzińska ◽  
Eliza Wasilewska ◽  
...  
Keyword(s):  
Duchenne Muscular Dystrophy ◽  
Physical Therapy ◽  
Muscular Dystrophy ◽  
Healthcare System ◽  
Online Survey ◽  
Young Men ◽  
The Mean ◽  
Respiratory Exercises

Background: The COVID-19 pandemic forced reorganization of the multidisciplinary healthcare system for Duchenne muscular dystrophy. Digital solutions seem to be optimal for providing rehabilitation at this time. The aim of this study was to investigate whether it is possible to conduct respiratory physical therapy with the use of telerehabilitation in Duchenne muscular dystrophy. Methods: The study was conducted during an online conference for families with DMD. During the physical therapy panel we showed the video with the instructions of respiratory exercises. All participants (n = 152) were asked to fill in the online survey evaluating the quality, acceptance, and understanding of the instructions. Results: The survey was filled in by 45 (29.6%) participants. The mean rating of satisfaction was 4.70/5, and for intelligibility was 4.78/5. Thirty-seven (82.2%) patients declared that they had performed the exercises, all caregivers declared that it was possible to perform the proposed exercises a few times a week or daily, and only two respondents replied to invitations to individual online sessions. Conclusions: Findings from the study show that respiratory telerehabilitation may be implemented for DMD patients; however, the interest in digital rehabilitation among caregivers of DMD boys in Poland is low. The reasons for this situation require further research.

scholarly journals Emotional Bonding and Sexual Activity During COVID-19 Lockdown: A Cross-National Pilot Study

2021 ◽  
pp. 263183182110274
Author(s):  
Deblina Roy ◽  
Sujita Kumar Kar ◽  
SM Yasir Arafat ◽  
Pawan Sharma ◽  
Russell Kabir
Keyword(s):  
Online Survey ◽  
Sampling Technique ◽  
Sexual Relationships ◽  
Sexually Active ◽  
Online Questionnaire ◽  
Cross Sectional ◽  
Emotional Bonding ◽  
Significant Difference ◽  
The Mean ◽  
Study Participants

Background: The COVID-19 pandemic and lockdown measures have affected the sexuality and emotional bonding among the couple across the world. Objectives: We aimed to assess the effects of the COVID-19 pandemic and lockdown on the married people’s emotional bonding and sexual relationships in 3 south Asian counties (Bangladesh, India, and Nepal). Methods: A cross-sectional online survey was conducted among Bangladesh, India, and Nepal residents from April 3 to April 15, 2020. The survey was designed in English. The participants were selected through convenience sampling technique, the link of the online questionnaire was shared with the participants. Only participants older than 18 years and above, married, and living with their spouses were included in the study. Results: A total number of 120 respondents were included finally for analysis from the participating countries (India, Nepal, and Bangladesh). The mean age of the participants was 35.42 (±5.73) years; the majority were males under the age of 40 years and had completed postgraduation as their qualification. Among the study participants, more than half (53.8%) of the women reported being sexually active during the lockdown, whereas 41% of the men reported being sexually active. Among the sexually active participants, most women (57.7%) reported that they perceived positive emotional bonding with their partners. Nevertheless, there was no significant difference observed when compared with men. There are variations in responses. However, no significant association was identified. Conclusion: There are a few insights from the study, that is, there was no significant difference found in almost 3 countries in emotional intimacy. There had been a trend that there is improved emotional bonding with their partners, although no significant difference was observed.

scholarly journals The impact of theory-based messages on COVID-19 vaccination intentions: a structured summary of a study protocol for a randomised controlled trial

Trials ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Ben Young ◽  
Marie Kotzur ◽  
Lauren Gatting ◽  
Carissa Bonner ◽  
Julie Ayre ◽  
...  
Keyword(s):  
Online Survey ◽  
Controlled Trial ◽  
Significant Proportion ◽  
General Information ◽  
School Level ◽  
Text And Image ◽  
Post Intervention ◽  
Full Protocol ◽  
The Impact ◽  
Illness Coherence

Abstract Objectives Uptake of vaccination against COVID-19 is key to controlling the pandemic. However, a significant proportion of people report that they do not intend to have a vaccine, often because of concerns they have about vaccine side effects or safety. This study will assess the impact of theory-based messages on COVID-19 vaccination intention, drawing on the Necessity-Concerns framework to address previously reported beliefs and concerns about COVID-19 vaccination, and assess whether hypothesised variables (illness coherence, perceived necessity and concerns) mediate change in vaccination intention. Trial design Prospective, parallel two-arm, individually randomised (1:1) trial. Participants Adults aged over 18 years, living in Scotland and not vaccinated for COVID-19. A quota sampling approach will be used with the aim of achieving a nationally representative sample on gender, region and ethnic group, with oversampling of individuals with no educational qualifications or with only school-level qualifications. Intervention and comparator Intervention: Brief exposure to online text and image-based messages addressing necessity beliefs and concerns about COVID-19 vaccination. Comparator: Brief exposure to online text and image-based messages containing general information about COVID-19 and COVID-19 vaccination. Main outcomes Primary outcome: Self-reported intention to receive a vaccine for COVID-19 if invited, immediately post-intervention. Secondary outcomes: Self-reported COVID-19 illness coherence, perceived necessity of a COVID-19 vaccine and concerns about a COVID-19 vaccine, immediately post-intervention. Randomisation Quasi-randomisation performed automatically by online survey software, by creating a variable derived from the number of seconds in the minute that the participant initiates the survey. Participants starting the survey at 0-14 or 30-44 seconds in the minute are allocated to the intervention and 15-29 or 45-59 seconds to the comparator. Blinding (masking) Participants will not be blinded to group assignment but will not be informed of the purpose of the study until they have completed the follow-up survey. Investigators will be blinded to allocation as all procedures will be undertaken digitally and remotely without any investigator contact with participants. Numbers to be randomised (sample size) A total of 1,094 will be randomised 1:1 into two groups with 547 individuals in each. Trial Status Protocol version number 1.0, 26th February 2021. Recruitment status: Not yet recruiting, set to start April 2021 and end April 2021. Trial registration ClinicalTrials.gov, NCT04813770, 24th March 2021. Full protocol The full protocol is attached as an additional file, accessible from the Trials website (Additional file 1). In the interest in expediting dissemination of this material, the familiar formatting has been eliminated; this Letter serves as a summary of the key elements of the full protocol.

scholarly journals Use of Artificial Intelligence to understand adults’ thoughts and behaviours relating to COVID-19

2021 ◽  
pp. 175791392097933
Author(s):  
SW Flint ◽  
A Piotrkowicz ◽  
K Watts
Keyword(s):  
Artificial Intelligence ◽  
Online Survey ◽  
Severe Illness ◽  
Free Text ◽  
Community Recovery ◽  
Substantial Impact ◽  
Lifestyle Behaviours ◽  
Artificial Intelligence Methods ◽  
High Concern ◽  
The Impact

Aims: The outbreak of severe acute respiratory syndrome coronavirus 2 (COVID-19) is a global pandemic that has had substantial impact across societies. An attempt to reduce infection and spread of the disease, for most nations, has led to a lockdown period, where people’s movement has been restricted resulting in a consequential impact on employment, lifestyle behaviours and wellbeing. As such, this study aimed to explore adults’ thoughts and behaviours in response to the outbreak and resulting lockdown measures. Methods: Using an online survey, 1126 adults responded to invitations to participate in the study. Participants, all aged 18 years or older, were recruited using social media, email distribution lists, website advertisement and word of mouth. Sentiment and personality features extracted from free-text responses using Artificial Intelligence methods were used to cluster participants. Results: Findings demonstrated that there was varied knowledge of the symptoms of COVID-19 and high concern about infection, severe illness and death, spread to others, the impact on the health service and on the economy. Higher concerns about infection, illness and death were reported by people identified at high risk of severe illness from COVID-19. Behavioural clusters, identified using Artificial Intelligence methods, differed significantly in sentiment and personality traits, as well as concerns about COVID-19, actions, lifestyle behaviours and wellbeing during the COVID-19 lockdown. Conclusions: This time-sensitive study provides important insights into adults’ perceptions and behaviours in response to the COVID-19 pandemic and associated lockdown. The use of Artificial Intelligence has identified that there are two behavioural clusters that can predict people’s responses during the COVID-19 pandemic, which goes beyond simple demographic groupings. Considering these insights may improve the effectiveness of communication, actions to reduce the direct and indirect impact of the COVID-19 pandemic and to support community recovery.

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