scholarly journals Clinical Desire for an Artificial Intelligence–Based Surgical Assistant System: Electronic Survey–Based Study

10.2196/17647 ◽  
2020 ◽  
Vol 8 (5) ◽  
pp. e17647
Author(s):  
Soo Jin Park ◽  
Eun Ji Lee ◽  
Se Ik Kim ◽  
Seong-Ho Kong ◽  
Chang Wook Jeong ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Laparoscopic Surgery ◽  
Operating Room ◽  
Online Survey ◽  
Clinical Decision ◽  
Electronic Survey ◽  
Conventional Laparoscopic ◽  
General Surgeons ◽  
Surgical Assistants ◽  
Surgical System

Background Techniques utilizing artificial intelligence (AI) are rapidly growing in medical research and development, especially in the operating room. However, the application of AI in the operating room has been limited to small tasks or software, such as clinical decision systems. It still largely depends on human resources and technology involving the surgeons’ hands. Therefore, we conceptualized AI-based solo surgery (AISS) defined as laparoscopic surgery conducted by only one surgeon with support from an AI-based surgical assistant system, and we performed an electronic survey on the clinical desire for such a system. Objective This study aimed to evaluate the experiences of surgeons who have performed laparoscopic surgery, the limitations of conventional laparoscopic surgical systems, and the desire for an AI-based surgical assistant system for AISS. Methods We performed an online survey for gynecologists, urologists, and general surgeons from June to August 2017. The questionnaire consisted of six items about experience, two about limitations, and five about the clinical desire for an AI-based surgical assistant system for AISS. Results A total of 508 surgeons who have performed laparoscopic surgery responded to the survey. Most of the surgeons needed two or more assistants during laparoscopic surgery, and the rate was higher among gynecologists (251/278, 90.3%) than among general surgeons (123/173, 71.1%) and urologists (35/57, 61.4%). The majority of responders answered that the skillfulness of surgical assistants was “very important” or “important.” The most uncomfortable aspect of laparoscopic surgery was unskilled movement of the camera (431/508, 84.8%) and instruments (303/508, 59.6%). About 40% (199/508, 39.1%) of responders answered that the AI-based surgical assistant system could substitute 41%-60% of the current workforce, and 83.3% (423/508) showed willingness to buy the system. Furthermore, the most reasonable price was US $30,000-50,000. Conclusions Surgeons who perform laparoscopic surgery may feel discomfort with the conventional laparoscopic surgical system in terms of assistant skillfulness, and they may think that the skillfulness of surgical assistants is essential. They desire to alleviate present inconveniences with the conventional laparoscopic surgical system and to perform a safe and comfortable operation by using an AI-based surgical assistant system for AISS.

scholarly journals Clinical Desire for an Artificial Intelligence–Based Surgical Assistant System: Electronic Survey–Based Study (Preprint)

2019 ◽  
Author(s):  
Soo Jin Park ◽  
Eun Ji Lee ◽  
Se Ik Kim ◽  
Seong-Ho Kong ◽  
Chang Wook Jeong ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Laparoscopic Surgery ◽  
Operating Room ◽  
Online Survey ◽  
Clinical Decision ◽  
Electronic Survey ◽  
Conventional Laparoscopic ◽  
General Surgeons ◽  
Surgical Assistants ◽  
Surgical System

BACKGROUND Techniques utilizing artificial intelligence (AI) are rapidly growing in medical research and development, especially in the operating room. However, the application of AI in the operating room has been limited to small tasks or software, such as clinical decision systems. It still largely depends on human resources and technology involving the surgeons’ hands. Therefore, we conceptualized AI-based solo surgery (AISS) defined as laparoscopic surgery conducted by only one surgeon with support from an AI-based surgical assistant system, and we performed an electronic survey on the clinical desire for such a system. OBJECTIVE This study aimed to evaluate the experiences of surgeons who have performed laparoscopic surgery, the limitations of conventional laparoscopic surgical systems, and the desire for an AI-based surgical assistant system for AISS. METHODS We performed an online survey for gynecologists, urologists, and general surgeons from June to August 2017. The questionnaire consisted of six items about experience, two about limitations, and five about the clinical desire for an AI-based surgical assistant system for AISS. RESULTS A total of 508 surgeons who have performed laparoscopic surgery responded to the survey. Most of the surgeons needed two or more assistants during laparoscopic surgery, and the rate was higher among gynecologists (251/278, 90.3%) than among general surgeons (123/173, 71.1%) and urologists (35/57, 61.4%). The majority of responders answered that the skillfulness of surgical assistants was “very important” or “important.” The most uncomfortable aspect of laparoscopic surgery was unskilled movement of the camera (431/508, 84.8%) and instruments (303/508, 59.6%). About 40% (199/508, 39.1%) of responders answered that the AI-based surgical assistant system could substitute 41%-60% of the current workforce, and 83.3% (423/508) showed willingness to buy the system. Furthermore, the most reasonable price was US $30,000-50,000. CONCLUSIONS Surgeons who perform laparoscopic surgery may feel discomfort with the conventional laparoscopic surgical system in terms of assistant skillfulness, and they may think that the skillfulness of surgical assistants is essential. They desire to alleviate present inconveniences with the conventional laparoscopic surgical system and to perform a safe and comfortable operation by using an AI-based surgical assistant system for AISS.

Awareness and Perception of Dentists Regarding Role and Future of Artificial Intelligence in Dentistry

2021 ◽  
Vol 15 (12) ◽  
pp. 3555-3558
Author(s):  
Isma Sajjad ◽  
Yawar Ali Abidi ◽  
Nabeel Baig ◽  
Humera Akhlak ◽  
Maham Muneeb Lone ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Online Survey ◽  
Clinical Decision ◽  
Utilization Rate ◽  
Cross Sectional Survey ◽  
Cross Sectional ◽  
Dental Practitioner ◽  
Cad Cam ◽  
Great Passion ◽  
Graduate Trainees

Background: Every single field preferred artificial intelligence with great passion and thereby the discipline of dental science is no exemption. Aims: To evaluate the awareness and perception of dentists regarding artificial intelligence among dentists working in Karachi Methods: The current online cross-sectional survey conducted in Karachi during july 2021 . The survey included house officers, post-graduate trainees, and general dental practitioner and specialist consultant dental surgeons of either gender. A questionnaire was adopted from an existing similar study and modifications were made according to our settings. The link of survey was created using Google Docs and disseminated through various open social media groups of dental practitioner in Karachi. Results: Total 118 complete responses were received with almost equal responses from males (n=56, 47.5%) and females (n=52.5%). The mean age of study participants was 30.3±5.9 years. 83(70.3%) had awareness of the artificial intelligence driven tools in dentistry. 75.9%, 77.1%, 10.8%, 28.9%, 39.8%, 2.4% and 10.8% reported the use of digital intraoral radiographs, CAD-CAM, CBCT, digital dental records, clinical decision support system and none of the tool in their practice respectively. All of the participants had opinion that AI applications should be part of dental trainings. Conclusion: The present survey showed that the majority had awareness of AI applications in dentistry and had positive perception regarding its future role but there was lacking in the utilization rate of AI tools in their practice. Therefore, it is recommended to attend AI trainings to bring and adapt the AI related changes in local settings. Keywords: Artificial intelligence, dentistry, online survey, perception, awareness, Karachi

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 Assessing the utility and attitudes toward molecular testing in neuro-oncology: a survey of the Society for Neuro-Oncology members

2021 ◽  
Author(s):  
Shannon Fortin Ensign ◽  
Maya Hrachova ◽  
Susan Chang ◽  
Maciej M Mrugala
Keyword(s):  
Online Survey ◽  
Clinical Decision Making ◽  
Unmet Needs ◽  
Practice Patterns ◽  
Response Rate ◽  
Clinical Decision ◽  
Molecular Testing ◽  
Newly Diagnosed ◽  
Tumor Boards ◽  
Oncology Practice

Abstract Background Molecular testing (MT) is utilized in neuro-oncology with increasing frequency. The aim of this study was to determine clinical practice patterns to acquire this information, interpret and utilize MT for patient care, and identify unmet needs in the practical clinical application of MT. Methods We conducted a voluntary online survey of providers within the Society for Neuro-Oncology (SNO) membership database between March and April 2019. Results We received 152 responses out of 2022 SNO members (7.5% of membership). 88.8% of respondents routinely order MT for newly diagnosed gliomas. Of those who do not, testing is preferentially performed in younger patients or those with midline tumors. 82.8% use MT in recurrent gliomas. Other common indications included: metastatic tumors, meningioma, and medulloblastoma. Many providers utilize more than one resource (36.0%), most frequently using in-house (41.8%) over commercially available panels. 78.1% used the results for clinical decision-making, with BRAF, EGFR, ALK, and H3K27 mutations most commonly directing treatment decisions. Approximately, half (48.5%) of respondents have molecular tumor boards at their institutions. Respondents would like to see SNO-endorsed guidelines on MT, organized lists of targeted agents available for specific mutations, a database of targetable mutations and clinical trials, and more educational programs on MT. Conclusion This survey was marked by several limitations including response rate and interpretation of MT. Among respondents, there is routine use of MT in Neuro-Oncology, however, there remains a need for increased guidance for providers to effectively incorporate the expanding genomic data resulting from MT into daily Neuro-Oncology practice.

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 Lessons from the COVID-19 Pandemic on the Use of Artificial Intelligence in Digital Radiology: The Submission of a Survey to Investigate the Opinion of Insiders

Healthcare ◽  
2021 ◽  
Vol 9 (3) ◽  
pp. 331
Author(s):  
Daniele Giansanti ◽  
Ivano Rossi ◽  
Lisa Monoscalco
Keyword(s):  
Artificial Intelligence ◽  
General Purpose ◽  
Point Of View ◽  
General Point ◽  
Thoracic Radiography ◽  
Digital Radiology ◽  
Electronic Survey ◽  
Radiology Technicians ◽  
Medical Radiology ◽  
Great Development

The development of artificial intelligence (AI) during the COVID-19 pandemic is there for all to see, and has undoubtedly mainly concerned the activities of digital radiology. Nevertheless, the strong perception in the research and clinical application environment is that AI in radiology is like a hammer in search of a nail. Notable developments and opportunities do not seem to be combined, now, in the time of the COVID-19 pandemic, with a stable, effective, and concrete use in clinical routine; the use of AI often seems limited to use in research applications. This study considers the future perceived integration of AI with digital radiology after the COVID-19 pandemic and proposes a methodology that, by means of a wide interaction of the involved actors, allows a positioning exercise for acceptance evaluation using a general purpose electronic survey. The methodology was tested on a first category of professionals, the medical radiology technicians (MRT), and allowed to (i) collect their impressions on the issue in a structured way, and (ii) collect their suggestions and their comments in order to create a specific tool for this professional figure to be used in scientific societies. This study is useful for the stakeholders in the field, and yielded several noteworthy observations, among them (iii) the perception of great development in thoracic radiography and CT, but a loss of opportunity in integration with non-radiological technologies; (iv) the belief that it is appropriate to invest in training and infrastructure dedicated to AI; and (v) the widespread idea that AI can become a strong complementary tool to human activity. From a general point of view, the study is a clear invitation to face the last yard of AI in digital radiology, a last yard that depends a lot on the opinion and the ability to accept these technologies by the operators of digital radiology.

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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