Artificial Intelligence in Skin Cancer Diagnostics: The Patients' Perspective

Abstract

Background: Artificial intelligence (AI) has shown promise in numerous experimental studies, particularly in skin cancer diagnostics. Translation of these findings into the clinic is the logical next step. This translation can only be successful if patients' concerns and questions are addressed suitably. We therefore conducted a survey to evaluate the patients' view of artificial intelligence in melanoma diagnostics in Germany, with a particular focus on patients with a history of melanoma. Participants and Methods: A web-based questionnaire was designed using LimeSurvey, sent by e-mail to university hospitals and melanoma support groups and advertised on social media. The anonymous questionnaire evaluated patients' expectations and concerns toward artificial intelligence in general as well as their attitudes toward different application scenarios. Descriptive analysis was performed with expression of categorical variables as percentages and 95% confidence intervals. Statistical tests were performed to investigate associations between sociodemographic data and selected items of the questionnaire. Results: 298 individuals (154 with a melanoma diagnosis, 143 without) responded to the questionnaire. About 94% [95% CI = 0.91-0.97] of respondents supported the use of artificial intelligence in medical approaches. 88% [95% CI = 0.85-0.92] would even make their own health data anonymously available for the further development of AI-based applications in medicine. Only 41% [95% CI = 0.35-0.46] of respondents were amenable to the use of artificial intelligence as stand-alone system, 94% [95% CI = 0.92-0.97] to its use as assistance system for physicians. In subgroup analyses, only minor differences were detectable. Respondents with a previous history of melanoma were more amenable to the use of AI applications for early detection even at home. They would prefer an application scenario where physician and AI classify the lesions independently. With respect to AI-based applications in medicine, patients were concerned about insufficient Jutzi et al. Patients' View on AI-Based Diagnosis data protection, impersonality and susceptibility to errors, but expected faster, more precise and unbiased diagnostics, less diagnostic errors and support for physicians. Conclusions: The vast majority of participants exhibited a positive attitude toward the use of artificial intelligence in melanoma diagnostics, especially as an assistance system.

Co-Design of a Trustworthy AI System in Healthcare: Deep Learning Based Skin Lesion Classifier

“…According to (Jutzi et al, 2020) 75% of patients would recommend an AI system to their families and friends. and 94% wish symbiosis of the physician with AI.…”

Odos Vėžio Diagnostika Ir Dirbtinis Intelektas

“…Šiuo metu yra tik keletas tyrimų, nagrinėjančių pacientų požiūrį bei dirbtinio intelekto vertinimą odos vėžio diagnostikoje, trūksta informacijos apie pacientų įžvelgiamą papildomą vertę. Literatūroje pateikiamos apklausos paprastai aprašo teigiamas pacientų reakcijas [20,21]. C. Nelson ir kt.…”

“…atliktame tyrime didžioji dalis dalyvių nurodė, jog jie palaiko dirbtinio intelekto naudojimą melanomos diagnostikai, manydami, jog taip diagnozė būtų nustatyta greičiau, o dirbtinis intelektas galėtų padėti gydytojams, tačiau jaudinosi dėl nepakankamos duomenų apsaugos, nuasmeninimo bei imlumo klaidoms. Pastebėta, jog pacientai, jau anksčiau sirgę melanoma, dirbtinį intelektą vertino palankiau [21]. Toliau plėtojant ir taikant šias technologijas, būtina atsižvelgti į pacientų išreikštas dvejones bei aktyviai dirbti, sprendžiant minėtas problemas (pvz., duomenų apsaugos), be to, svarbu atlikti daugiau pacientų požiūrio bei dirbtinio intelekto vertinimo tyrimų.…”

Veterinary Experiences can Inform One Health Strategies for Animal Coronaviruses

“…Veterinarians and researchers have identified animal coronaviruses that can adapt to new hosts and also change over time within an established host. Examples of these processes in farmed and wild animals abound (Frutos et al 2020a ; Leroy et al 2020 ; Bartlett et al 2021 ; Halfmann et al 2020 ). Porcine Epidemic Diarrhea Virus (PEDV) was first reported in pigs in the 1970s in the United Kingdom.…”