Designing AINA - Intercultural Human-Centered Design of an AI-based Application for Supporting the Diagnosis of Female Genital Schistosomiasis

Lehmann, Nicolas J.; Karagulle, Muhammed-Ugur; Meurer, Pauline; Niedermeyer, Elen; Vidishiqi, Petrit; Pysz, Laura; Kreb, Marlene; Muth, Lea R.; Feldmeier, Hermann; Sahondra, Bodo Randrianasolo; Onintsoa, Oliva Rabozakandraina Tiana; Voisard, Agnès; Schuster, Angela

doi:10.1109/ichi54592.2022.00065

Cited by 2 publications

(4 citation statements)

References 19 publications

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“…It is, therefore, important to highlight that currently developed tools can be adapted for local pilot among healthcare professionals in the study area, to improve health workforce capacity and contribute to alleviating the neglect of FGS. This training should also be complemented with provision of appropriate diagnostics and on-site competence building for qualified health care professionals on colposcopy, as well as diagnosis of pathognomonic lesions using diagnostic atlas or Artificial Intelligence (AI) applications [ 43 ]…”

Section: Discussionmentioning

confidence: 99%

Profiling the knowledge of female medical/para-medical students, and expertise of health care professionals on female genital schistosomiasis in Anambra, South Eastern Nigeria

et al. 2023

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Background Female genital schistosomiasis (FGS) is a largely neglected tropical disease (NTD), with little or no attention in the primary health care unit. Towards building momentum to address this challenge, we investigated the perception of medical and para-medical students about FGS, as well as the expertise of health care professionals in Anambra State, Nigeria. Methodology We conducted a cross-sectional survey among 587 female medical and para-medical university students (MPMS), and 65 health care professionals (HCPs) saddled with the responsibility of delivering care for schistosomiasis-affected persons. Pretested questionnaires were administered to document the awareness and knowledge about the disease. In addition, the expertise of HCPs vis-à-vis suspicion of FGS and management of FGS patients during routine health care service were documented. Data were subjected to descriptive, chi-square tests and regression analysis in R software. Results Over half of the students recruited; 54.2% for schistosomiasis and 58.1% for FGS, were not aware of the disease. Knowledge about schistosomiasis was associated with student’s year of study, with those in 2nd (OR: 1.66, 95% CI: 1.0, 2.7), 4th (OR: 1.97, 95% CI: 1.2, 3.2), and 6th (OR: 5.05, 95% CI: 1.2, 34.2) year having higher likelihoods of been more informed about schistosomiasis. For HCPs, we observed a contrastingly high knowledge about schistosomiasis (96.9%), but low knowledge about FGS (61.9%). Knowledge for both schistosomiasis and FGS was not associated with year of practice and expertise (95% OR included 1, p > 0.05). A considerable proportion (>40%) of the HCPs never suspected schistosomiasis during routine clinical diagnosis of patients who presented probable FGS symptoms (p < 0.05). Similarly, only 20% were certain about the use of praziquantel for treating FGS, and about 35% were uncertain of the eligibility criteria and dosage regimens. Commodities for managing FGS were also largely unavailable in about 39% of the health facilities where the HCPs operate. Conclusion Awareness and knowledge about FGS among MPMS and HCPs were poor in Anambra, Nigeria. It is therefore important to invest in innovative methods of building capacity of MPMS and HCPs, with complementary provision of necessary diagnostics to perform colposcopy, as well as competence to diagnose pathognomonic lesions using diagnostic atlas or Artificial Intelligence (AI).

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Section: Discussionmentioning

confidence: 99%

Profiling the knowledge of female medical/para-medical students, and expertise of health care professionals on female genital schistosomiasis in Anambra, South Eastern Nigeria

et al. 2023

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“… [ [199] , [200] , [201] ] AINA Diagnosing Female Genital Schistosomiasis (FGS); recognizes FGS-related lesions in patient photos, provides educational support, and continuously enhances diagnostic accuracy. [ 202 ] Schistoscope Uses AI with a UNET-based deep neural network for automatic detection of Schistosoma haematobium eggs in urine. Operates semi- or fully automated, offering reliability and precise counting [ 202 , 203 , 204 ] 3S Technology Integration of GPS, Remote Sensing, and Geographical Information System (GIS) for identifying Schistosoma risk factors, mapping prevalence areas, and evaluating O. hupensis habitat and transmission risks.…”

Section: Applications Of Artificial Intelligence In the Detection Of ...mentioning

confidence: 99%

“… [ 202 ] Schistoscope Uses AI with a UNET-based deep neural network for automatic detection of Schistosoma haematobium eggs in urine. Operates semi- or fully automated, offering reliability and precise counting [ 202 , 203 , 204 ] 3S Technology Integration of GPS, Remote Sensing, and Geographical Information System (GIS) for identifying Schistosoma risk factors, mapping prevalence areas, and evaluating O. hupensis habitat and transmission risks. [ [205] , [206] , [207] , [208] ] AI-DP Prototype AI-based digital pathology for detecting soil-transmitted helminth and intestinal Schistosoma eggs; involves whole slide imaging (WSI) scanner, deep learning and data reporting system.…”

Section: Applications Of Artificial Intelligence In the Detection Of ...mentioning

confidence: 99%

“…The app employs a reinforcement learning feedback loop to continuously enhance diagnostic accuracy. Operating in rural African areas where FGS is endemic, AINA's user-friendly interfaces cater to local doctors, nurses, and midwives and FGS images captured in the field contribute to refining AI models [ 202 ].…”

Section: Applications Of Artificial Intelligence In the Detection Of ...mentioning

confidence: 99%

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A comprehensive exploration of schistosomiasis: Global impact, molecular characterization, drug discovery, artificial intelligence and future prospects

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et al. 2024

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Designing AINA - Intercultural Human-Centered Design of an AI-based Application for Supporting the Diagnosis of Female Genital Schistosomiasis

Cited by 2 publications

References 19 publications

Profiling the knowledge of female medical/para-medical students, and expertise of health care professionals on female genital schistosomiasis in Anambra, South Eastern Nigeria

Profiling the knowledge of female medical/para-medical students, and expertise of health care professionals on female genital schistosomiasis in Anambra, South Eastern Nigeria

A comprehensive exploration of schistosomiasis: Global impact, molecular characterization, drug discovery, artificial intelligence and future prospects

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