• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.1
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• pp.115-123
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• 2024

The purpose of this study is to contribute to how the advantages of artificial intelligence (AI) services and the associated limitations can be simultaneously overcome, using the keywords AI and risk management. To achieve this, two cases were introduced: (1) presenting a risk monitoring process utilizing AI and (2) introducing an operational toolkit to minimize the emerging limitations in the development and operation of AI services. Through case analysis, the following implications are proposed. First, as AI services deeply influence our lives, the process are needed to minimize the emerging limitations. Second, for effective risk management monitoring using AI, priority should be given to obtaining suitable and reliable data. Third, to overcome the limitations arising in the development and operation of AI services, the application of a risk management process at each stage of the workflow, requiring continuous monitoring, is essential. This study is a research effort on approaches to minimize limitations provided by advancing artificial intelligence (AI). It can contribute to research on risk management in the future growth and development of the related market, examining ways to mitigate limitations posed by evolving AI technologies.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.2
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• pp.861-865
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• 2014

Background: High risk HPV (HR-HPV) testing has been recommended as an effective tool along with cytology screening in identification of cervical intraepithelial lesions (CINs) and prevention of their progress towards invasive cervical cancer. The aim of this study was to assess the HR-HPV DNA status by Hybrid Capture 2 (HC2) assay in healthy asymptomatic women of North-East India. Materials and Methods: This study examined cervical cell samples of forty three (n=43) healthy women by HC2 assay. A High Risk HPV DNA kit (Qiagen) was used which can detect 13 high risk HPV types: 16, 18, 31, 33, 35, 39, 45, 51, 52, 56, 58, 59 and 68. Results: The mean relative light units (RLU) for samples was in the range of 141-5, 94, 619. HR-HPV DNA was confirmed in 16% (7/43) of participant women samples. Among demographic and clinical parameters, menstrual irregularity (p=0.039) and infection history (p=0.028) has shown statistically significant differences between the HR-HPV-positive and negative groups. In the HR-HPV positive group, two women were confirmed for CINs after colposcopy and histopathologic examination. Conclusions: We suggest that there may be an association between irregular menstruation and infection history of the urogenital tract with HR-HPV DNA prevalence in North-East Indian asymptomatic women. HC2 assay can be a valuable tool for HR-HPV screening.