Handan Kaya

814 total citations
48 papers, 536 citations indexed

About

Handan Kaya is a scholar working on Oncology, Pathology and Forensic Medicine and Cancer Research. According to data from OpenAlex, Handan Kaya has authored 48 papers receiving a total of 536 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Oncology, 15 papers in Pathology and Forensic Medicine and 13 papers in Cancer Research. Recurrent topics in Handan Kaya's work include Breast Lesions and Carcinomas (15 papers), Radiomics and Machine Learning in Medical Imaging (9 papers) and Breast Cancer Treatment Studies (9 papers). Handan Kaya is often cited by papers focused on Breast Lesions and Carcinomas (15 papers), Radiomics and Machine Learning in Medical Imaging (9 papers) and Breast Cancer Treatment Studies (9 papers). Handan Kaya collaborates with scholars based in Türkiye, Italy and Hungary. Handan Kaya's co-authors include Erkin Arıbal, Mustafa Ümit Uğurlu, Bahadır M. Güllüoğlu, Ayşe Özer, Mustafa Akkіprіk, Perran Fulden Yumuk, Süheyla Bozkurt, Esin Kotiloğlu, Mustafa B.A. Djamgoz and Maria Pia Foschini and has published in prestigious journals such as SHILAP Revista de lepidopterología, American Journal of Roentgenology and Breast Cancer Research and Treatment.

In The Last Decade

Handan Kaya

45 papers receiving 520 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Handan Kaya Türkiye 16 160 156 150 146 138 48 536
Christian R. De Potter Belgium 13 106 0.7× 252 1.6× 74 0.5× 175 1.2× 136 1.0× 17 585
Yozo Kokawa Japan 11 109 0.7× 161 1.0× 116 0.8× 104 0.7× 76 0.6× 32 429
Wen Wei China 13 202 1.3× 262 1.7× 65 0.4× 166 1.1× 86 0.6× 21 551
Emma J. Groen Netherlands 9 205 1.3× 243 1.6× 212 1.4× 89 0.6× 49 0.4× 15 485
Katharina Tiemann Germany 14 167 1.0× 294 1.9× 124 0.8× 141 1.0× 42 0.3× 35 552
Jeoung Won Bae South Korea 18 291 1.8× 214 1.4× 164 1.1× 149 1.0× 112 0.8× 67 890
Nobuko Tamura Japan 14 122 0.8× 172 1.1× 101 0.7× 100 0.7× 17 0.1× 39 455
Paola Ferro Italy 15 81 0.5× 125 0.8× 101 0.7× 132 0.9× 103 0.7× 50 588
Nair Lopes Portugal 14 164 1.0× 312 2.0× 253 1.7× 316 2.2× 24 0.2× 18 722
Page Dl United States 13 154 1.0× 122 0.8× 142 0.9× 94 0.6× 39 0.3× 23 496

Countries citing papers authored by Handan Kaya

Since Specialization
Citations

This map shows the geographic impact of Handan Kaya's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Handan Kaya with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Handan Kaya more than expected).

Fields of papers citing papers by Handan Kaya

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Handan Kaya. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Handan Kaya. The network helps show where Handan Kaya may publish in the future.

Co-authorship network of co-authors of Handan Kaya

This figure shows the co-authorship network connecting the top 25 collaborators of Handan Kaya. A scholar is included among the top collaborators of Handan Kaya based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Handan Kaya. Handan Kaya is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
2.
Uğurlu, Mustafa Ümit, et al.. (2023). Prediction of nipple involvement in breast cancer after neoadjuvant chemotherapy: Should we rely on breast MRI to preserve the nipple?. Breast Cancer Research and Treatment. 201(3). 417–424.
3.
Güllüoğlu, Bahadır M., Ebru Taştekin, Handan Kaya, et al.. (2023). Conventional Tools for Predicting Satisfactory Response to Neoadjuvant Chemotherapy in HR+/HER2− Breast Cancer Patients. Breast Care. 18(5). 344–353. 1 indexed citations
4.
Foschini, Maria Pia, et al.. (2022). Breast lesions with myoepithelial phenotype. Histopathology. 82(1). 53–69. 2 indexed citations
5.
Köstek, Osman, Tuğba Akın Telli, Özlem Erçelep, et al.. (2021). Predictive value of 18F-FDG PET/CT indices on extensive residual cancer burden in breast cancer patients treated with neoadjuvant chemotherapy. Revista Española de Medicina Nuclear e Imagen Molecular (English Edition). 41(3). 171–178. 2 indexed citations
6.
Uğurlu, Mustafa Ümit, et al.. (2020). Prognostic Role of Immune Markers in Triple Negative Breast Carcinoma. Pathology & Oncology Research. 26(4). 2733–2745. 18 indexed citations
7.
Seven, İpek Erbarut, Handan Kaya, Mustafa Ümit Uğurlu, et al.. (2020). PIK3CA and TP53 MUTATIONS and SALL4 , PTEN and PIK3R1 GENE EXPRESSION LEVELS in BREAST CANCER. Turkish Journal of Biochemistry. 45(5). 515–523. 1 indexed citations
8.
Foschini, Maria Pia, Rossella Miglio, Chiara Baldovini, et al.. (2019). Pre-operative management of Pleomorphic and florid lobular carcinoma in situ of the breast: Report of a large multi-institutional series and review of the literature. European Journal of Surgical Oncology. 45(12). 2279–2286. 33 indexed citations
9.
Alan, Özkan, Tuğba Akın Telli, Özlem Erçelep, et al.. (2018). A case of primary squamous cell carcinoma of the breast with pathologic complete response after neoadjuvant chemotherapy. Current Problems in Cancer. 43(4). 308–311. 9 indexed citations
10.
Fraser, Scott P., Esra Battaloğlu, Handan Kaya, et al.. (2017). Neonatal Nav1.5 protein expression in normal adult human tissues and breast cancer. Pathology - Research and Practice. 213(8). 900–907. 31 indexed citations
11.
Özmen, Tolga, Bahadır M. Güllüoğlu, Handan Kaya, et al.. (2016). Correlation between the DNA methylation and gene expression of IGFBP5 in breast cancer. Breast Disease. 36(4). 123–131. 10 indexed citations
12.
13.
Akkіprіk, Mustafa, et al.. (2015). Identification of Differentially Expressed IGFBP5-Related Genes in Breast Cancer Tumor Tissues Using cDNA Microarray Experiments. Genes. 6(4). 1201–1214. 21 indexed citations
14.
Arıbal, Erkin, et al.. (2014). Value of Strain Elastography Ultrasound in Differentiation of Breast Masses and Histopathologic Correlation. SHILAP Revista de lepidopterología. 10(4). 234–238. 8 indexed citations
15.
Bebi̇toğlu, Berna Terzi̇oğlu, et al.. (2012). Role of Melatonin and Luzindole in Rat Mammary Cancer. Journal of Investigative Surgery. 25(6). 345–353. 5 indexed citations
16.
Kaya, Handan, et al.. (2008). Apocrine carcinomas of the breast in Turkish women: Hormone receptors, c-erbB-2 and p53 immunoexpression. Pathology - Research and Practice. 204(6). 367–371. 8 indexed citations
17.
Akkіprіk, Mustafa, Özgür Sönmez, Bahadır M. Güllüoğlu, et al.. (2008). Analysis of p53 Gene Polymorphisms and Protein Over-expression in Patients with Breast Cancer. Pathology & Oncology Research. 15(3). 359–368. 29 indexed citations
18.
Sarı, Murat, et al.. (2006). Condylar metastasis involving TMJ and TMJ dislocation presenting as the initial manifestation of squamous lung cancer. Dspace Repository (Marmara Üniversitesi). 42(6). 224–226. 6 indexed citations
19.
Kaya, Handan, Erkin Arıbal, & Cumhur Yeğen. (2002). Apocrine differentiation in invasive pleomorphic lobular carcinoma with in situ ductal and lobular apocrine carcinoma: Case report. Pathology & Oncology Research. 8(2). 151–152. 8 indexed citations
20.
Kaya, Handan, et al.. (2001). Her-2/neu gene amplification compared with HER-2/neu protein overexpression on ultrasound guided core-needle biopsy specimens of breast carcinoma. Pathology & Oncology Research. 7(4). 279–283. 8 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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