Acceptability of artificial intelligence for cervical cancer screening in Dschang, Cameroon: a qualitative study on patient perspectives.

BACKGROUND: Cervical cancer is the fourth most frequent cancer among women, with 90% of cervical cancer-related deaths occurring in low- and middle-income countries like Cameroon. Visual inspection with acetic acid is often used in low-resource settings to screen for cervical cancer; however, its accuracy can be limited. To address this issue, the Swiss Federal Institute of Technology Lausanne and the University Hospitals of Geneva are collaborating to develop an automated smartphone-based image classifier that serves as a computer aided diagnosis tool for cancerous lesions. The primary objective of this study is to explore the acceptability and perspectives of women in Dschang regarding the usage of a screening tool for cervical cancer relying on artificial intelligence. A secondary objective is to understand the preferred form and type of information women would like to receive regarding this artificial intelligence-based screening tool. METHODS: A qualitative methodology was employed to gain better insight into the women's perspectives. Participants, aged between 30 and 49 were invited from both rural and urban regions and semi-structured interviews using a pre-tested interview guide were conducted. The focus groups were divided on the basis of level of education, as well as HPV status. The interviews were audio-recorded, transcribed, and coded using the ATLAS.ti software. RESULTS: A total of 32 participants took part in the six focus groups, and 38% of participants had a primary level of education. The perspectives identified were classified using an adapted version of the Technology Acceptance Model. Key factors influencing the acceptability of artificial intelligence include privacy concerns, perceived usefulness, and trust in the competence of providers, accuracy of the tool as well as the potential negative impact of smartphones. CONCLUSION: The results suggest that an artificial intelligence-based screening tool for cervical cancer is mostly acceptable to the women in Dschang. By ensuring patient confidentiality and by providing clear explanations, acceptance can be fostered in the community and uptake of cervical cancer screening can be improved. TRIAL REGISTRATION: Ethical Cantonal Board of Geneva, Switzerland (CCER, N°2017-0110 and CER-amendment n°4) and Cameroonian National Ethics Committee for Human Health Research (N°2022/12/1518/CE/CNERSH/SP). NCT: 03757299.

Globally, cervical cancer is the fourth most frequent cancer among women. However, 90% of all deaths caused by cervical cancer occur in low-and middle-income countries. Methods traditionally used in settings like Cameroon to detect cervical cancer unfortunately lack accuracy. Therefore, researchers at the Swiss Federal Institute of Technology Lausanne and the University Hospitals of Geneva are developing an artificial intelligence-based computer aided diagnosis tool to detect pre-cancerous lesions using a smartphone application. The aim of this study was to explore the acceptability and perspectives regarding an AI-based tool for cervical cancer screening for women in Dschang, a city in the west of Cameroon. A qualitative methodology was conducted with six focus groups and a total of 32 participants. The main concerns highlighted by the study are related to privacy, trust in the ability of the healthcare providers, accuracy of the tool as well as the potential negative impact of smartphones. In conclusion, our results show that a computer aided diagnosis tool using artificial intelligence is mostly acceptable to women in Dschang, as long as their confidentiality is preserved, and they are provided with clear explanations beforehand.

The status of refrigeration solutions for last mile vaccine delivery in low-income settings.

Recommendations for storage of most vaccines imply a continuous exposure to a temperature range between 0 °C and 10 °C, from the production to the administration to beneficiaries. According to the World Health Organization, more than 50% of vaccines are wasted around the world. Discontinuities of the cold chain in low-income settings where electricity is scarce contributes to this wastage. Recently, several advances have been made in cooling technologies to store and transport vaccines. This paper presents an overview of refrigeration technologies based on scientific publications, industry white papers and other grey literature. With a focus on vaccine transport, we briefly describe each refrigeration method, its best performing available devices as well as the outstanding research challenges in order to further improve its performance.

Study protocol for a two-site clinical trial to validate a smartphone-based artificial intelligence classifier identifying cervical precancer and cancer in HPV-positive women in Cameroon.

INTRODUCTION: Cervical cancer remains a major public health challenge in low- and middle-income countries (LMICs) due to financial and logistical issues. WHO recommendation for cervical cancer screening in LMICs includes HPV testing as primary screening followed by visual inspection with acetic acid (VIA) and treatment. However, VIA is a subjective procedure dependent on the healthcare provider's experience. Its accuracy can be improved by computer-aided detection techniques. Our aim is to assess the performance of a smartphone-based Automated VIA Classifier (AVC) relying on Artificial Intelligence to discriminate precancerous and cancerous lesions from normal cervical tissue. METHODS: The AVC study will be nested in an ongoing cervical cancer screening program called "3T-study" (for Test, Triage and Treat), including HPV self-sampling followed by VIA triage and treatment if needed. After application of acetic acid on the cervix, precancerous and cancerous cells whiten more rapidly than non-cancerous ones and their whiteness persists stronger overtime. The AVC relies on this key feature to determine whether the cervix is suspect for precancer or cancer. In order to train and validate the AVC, 6000 women aged 30 to 49 years meeting the inclusion criteria will be recruited on a voluntary basis, with an estimated 100 CIN2+, calculated using a confidence level of 95% and an estimated sensitivity of 90% +/-7% precision on either side. Diagnostic test performance of AVC test and two current standard tests (VIA and cytology) used routinely for triage will be evaluated and compared. Histopathological examination will serve as reference standard. Participants' and providers' acceptability of the technology will also be assessed. The study protocol was registered under ClinicalTrials.gov (number NCT04859530). EXPECTED RESULTS: The study will determine whether AVC test can be an effective method for cervical cancer screening in LMICs.