Translatability Analysis of National Institutes of Health–Funded Biomedical Research That Applies Artificial Intelligence

Eweje, Feyisope; Byun, Suzie; Chandra, Rajat; Hu, Fengling; Kamel, Ihab R.; Zhang, Paul; Jiao, Zhicheng; Bai, Harrison X.

doi:10.1001/jamanetworkopen.2021.44742

Cited by 5 publications

(7 citation statements)

References 39 publications

(79 reference statements)

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“…HPV testing was done in ISO-accredited laboratories using Luminex xMAP (Luminex Corporation; detecting HPV genotypes 16,18,31,33,35,39,45,51,52,53,56,58,59,66,68,82)…”

Section: Jama Network Open | Infectious Diseasesmentioning

confidence: 99%

“…The HPV genotypes were classified using the systems proposed by the International Agency for Research on Cancer, where the 12 HPV types 16,18,31,33,35,39,45,51,52,56,58, and 59 were classified as high-risk (with HPV type 68 as probably high risk) and the HPV types 26, 53, 66, 67, 70, 73, and 82 as possibly high risk. 24…”

Section: High-risk Hpv Infectionmentioning

confidence: 99%

“…A recent study assessing translatability (from algorithms that perform well on standardized data sets to operational systems demonstrated an improvement in clinical outcomes 15 ) of AI applications brought about electronic health record-based research among those with the highest promise for health improvement. 16 We applied data mining methodology on data from nationwide and a population-based electronic health record (EHR) system to examine the prevaccination prevalence of hrHPV and the distribution of HPV types by cervical cytology grade in the Estonian female population. In addition, we evaluated the potential effects of HPV vaccines in Estonia.…”

Section: Introductionmentioning

confidence: 99%

“…Various types of medical data (electronic health records, billing data, registries) are generated at a high speed and the growth in research involving data mining (DM) and artificial intelligence (AI) in health care has been exponential. A recent study assessing translatability (from algorithms that perform well on standardized data sets to operational systems demonstrated an improvement in clinical outcomes) of AI applications brought about electronic health record–based research among those with the highest promise for health improvement …”

Section: Introductionmentioning

confidence: 99%

“…Prevaccination Prevalence of Type-Specific HPV Infection by Grade of Cervical Cytology in Estonia Elimination of all vaccine-covered HPV types (HPV16,18,31,33, 45, 52, 58) was estimated to reduce the number of women with high-grade cytology by 50.5% (95% CI, 47.4%-53.6%) and low-grade cytology by 27.8% (95% CI, 26.3%-29.3%), giving an overall estimated reduction of 33.1% (95% CI, 31.7%-34.5%) in the number of women with abnormal cytology. The remaining hrHPV types(HPV 35, 39, 51, 56, 59, 68) were estimated to be 14.2% (95% CI, 13.0%-15.4%) of LSIL cases and 11.7% (95% CI 9.8%-13.8%) of HSIL cases.…”

mentioning

confidence: 99%

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Prevaccination Prevalence of Type-Specific Human Papillomavirus Infection by Grade of Cervical Cytology in Estonia

et al. 2023

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ImportanceLarge-scale data on type-specific human papillomavirus (HPV) prevalence and disease burden worldwide are needed to guide cervical cancer prevention efforts. Promoting the research and application of health care big data has become a key factor in modern medical research.ObjectiveTo examine the prevaccination prevalence of high-risk HPV (hrHPV) and type distribution by cervical cytology grade in Estonia.Design, Setting, and ParticipantsThis cross-sectional study used text mining and the linking of data from electronic health records and health care claims to examine type-specific hrHPV positivity in Estonia from 2012 to 2019. Participants were women aged at least 18 years. Statistical analysis was performed from September 2021 to August 2022.Main Outcomes and MeasuresType-specific hrHPV positivity rate by cervical cytological grade.ResultsA total of 11 017 cases of cervical cytology complemented with data on hrHPV testing results between 2012 and 2019 from 66 451 women aged at least 18 years (mean [SD] age, 48.1 [21.0] years) were included. The most common hrHPV types were HPV16, 18, 31, 33, 51 and 52, which accounted for 73.8% of all hrHPV types detected. There was a marked decline in the positivity rate of hrHPV infection with increasing age, but the proportion did not vary significantly based on HPV type. Implementation of nonavalent prophylactic vaccination was estimated to reduce the number of women with high-grade cytology by 50.5% (95% CI, 47.4%-53.6%) and the number with low-grade cytology by 27.8% (95% CI, 26.3%-29.3%), giving an overall estimated reduction of 33.1% (95% CI, 31.7%-34.5%) in the number of women with precancerous cervical cytology findings.Conclusions and RelevanceIn this cross-sectional study, text mining and natural language processing techniques allowed the detection of precursors to cervical cancer based on data stored by the nationwide health system. These findings contribute to the literature on type-specific HPV distribution by cervical cytology grade and document that α-9 phylogenetic group HPV types 16, 31, 33, 52 and α-7 phylogenetic group HPV 18 are the most frequently detected in normal-to-high-grade precancerous lesions in Estonia.

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“…HPV testing was done in ISO-accredited laboratories using Luminex xMAP (Luminex Corporation; detecting HPV genotypes 16,18,31,33,35,39,45,51,52,53,56,58,59,66,68,82)…”

Section: Jama Network Open | Infectious Diseasesmentioning

confidence: 99%