Naveena Singh Data-verified
Affiliation confirmed via AI analysis of OpenAlex, ORCID, and web sources.
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Biography and Research Information
OverviewAI-generated summary
Naveena Singh's research focuses on gynecological cancers, particularly ovarian and endometrial cancers. Her work investigates diagnostic and prognostic markers, as well as the application of advanced computational methods in pathology. She has contributed to studies examining population screening for ovarian cancer and changes in the classification of female genital tumors.
Singh's publications include research on the role of p53 immunohistochemistry and tertiary lymphoid structures in endometrial cancer prognosis. She has also been involved in developing and applying deep learning models for the molecular classification of endometrial cancer and the histotype diagnosis of ovarian carcinoma from histopathology images. Her collaborators include David N. Church from the University of Arkansas for Medical Sciences, with whom she has co-authored multiple publications.
With a highly cited researcher designation, Singh has an h-index of 64 and over 16,900 citations across her 437 publications, indicating a significant body of work in her field. She is noted as recently active in her research endeavors.
Metrics
- h-index: 64
- Publications: 437
- Citations: 16,943
Selected Publications
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Estimating the ovarian cancer CA-125 preclinical detectable phase, in-vivo tumour doubling time, and window for detection in early stage: an exploratory analysis of UKCTOCS (2025)
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The genomic trajectory of ovarian high‐grade serous carcinoma can be observed in <scp>STIC</scp> lesions (2024)
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AI-based histopathology image analysis reveals a distinct subset of endometrial cancers (2024)
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The spectrum of oestrogen receptor expression in endometrial carcinomas of no specific molecular profile (2024)
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Prognostic impact and causality of age on oncological outcomes in women with endometrial cancer: a multimethod analysis of the randomised PORTEC-1, PORTEC-2, and PORTEC-3 trials (2024)
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High concordance of molecular subtyping between pre-surgical biopsy and surgical resection specimen (matched-pair analysis) in patients with vulvar squamous cell carcinoma using p16- and p53-immunostaining (2024)
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Deep learning-based segmentation of multisite disease in ovarian cancer (2023)
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Ovarian cancer symptoms in pre-clinical invasive epithelial ovarian cancer – An exploratory analysis nested within the UK Collaborative Trial of Ovarian Cancer Screening (UKCTOCS) (2023)
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FIGO 2023 endometrial cancer staging: too much, too soon? (2023)
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Integrated radiogenomics models predict response to neoadjuvant chemotherapy in high grade serous ovarian cancer (2023)
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Clinical Behavior and Molecular Landscape of Stage I p53-Abnormal Low-Grade Endometrioid Endometrial Carcinomas (2023)
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Perceptions of Controversies and Unresolved Issues in the 2014 FIGO Staging System for Endometrial Cancer: Survey Results From Members of the International Society of Gynecological Pathologists and International Gynecologic Cancer Society (2023)
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Tumour stage, treatment, and survival of women with high-grade serous tubo-ovarian cancer in UKCTOCS: an exploratory analysis of a randomised controlled trial (2023)
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Biallelic <i>Dicer1</i> Mutations in the Gynecologic Tract of Mice Drive Lineage-Specific Development of <i>DICER1</i> Syndrome–Associated Cancer (2023)
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Microsatellite instability in non-endometrioid ovarian epithelial tumors: a study of 400 cases comparing immunohistochemistry, PCR, and NGS based testing with mutation status of MMR genes (2023)
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