António Polónia

3.3k total citations · 1 hit paper
49 papers, 1.7k citations indexed

About

António Polónia is a scholar working on Radiology, Nuclear Medicine and Imaging, Artificial Intelligence and Oncology. According to data from OpenAlex, António Polónia has authored 49 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Radiology, Nuclear Medicine and Imaging, 21 papers in Artificial Intelligence and 16 papers in Oncology. Recurrent topics in António Polónia's work include AI in cancer detection (21 papers), Radiomics and Machine Learning in Medical Imaging (13 papers) and Monoclonal and Polyclonal Antibodies Research (11 papers). António Polónia is often cited by papers focused on AI in cancer detection (21 papers), Radiomics and Machine Learning in Medical Imaging (13 papers) and Monoclonal and Polyclonal Antibodies Research (11 papers). António Polónia collaborates with scholars based in Portugal, Spain and Italy. António Polónia's co-authors include Catarina Eloy, Paulo Aguiar, Guilherme Aresta, Teresa Araújo, Aurélio Campilho, José Rouco, Eduardo Castro, Fernando Schmitt, Joana Paredes and Celso A. Reis and has published in prestigious journals such as Nature Communications, SHILAP Revista de lepidopterología and PLoS ONE.

In The Last Decade

António Polónia

44 papers receiving 1.6k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Classification of breast cancer histology images using Convolutional Neural Networks

2017 648 citations Teresa Araújo, Guilherme Aresta et al. PLoS ONE profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
António Polónia Portugal	18	977	809	397	366	361	49	1.7k
Cleo‐Aron Weis Germany	22	844 0.9×	713 0.9×	375 0.9×	703 1.9×	315 0.9×	71	2.3k
Catarina Eloy Portugal	24	863 0.9×	673 0.8×	417 1.1×	413 1.1×	327 0.9×	109	2.3k
Riku Turkki Finland	20	551 0.6×	496 0.6×	336 0.8×	541 1.5×	229 0.6×	35	1.6k
Daisuke Komura Japan	18	510 0.5×	402 0.5×	434 1.1×	306 0.8×	231 0.6×	63	1.5k
Yinyin Yuan United Kingdom	25	531 0.5×	537 0.7×	963 2.4×	726 2.0×	155 0.4×	67	2.3k
Rupert Ecker Austria	22	562 0.6×	163 0.2×	364 0.9×	793 2.2×	241 0.7×	35	2.0k
Inka Zörnig Germany	15	469 0.5×	602 0.7×	352 0.9×	618 1.7×	131 0.4×	37	1.4k
Panu E. Kovanen Finland	26	422 0.4×	415 0.5×	627 1.6×	691 1.9×	91 0.3×	44	2.3k
Stephan Wienert Germany	16	322 0.3×	186 0.2×	233 0.6×	419 1.1×	171 0.5×	32	1.4k
Antonia Charchanti Greece	16	431 0.4×	135 0.2×	313 0.8×	188 0.5×	285 0.8×	40	1.4k

Countries citing papers authored by António Polónia

Since Specialization

Citations

This map shows the geographic impact of António Polónia'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 António Polónia with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites António Polónia more than expected).

Fields of papers citing papers by António Polónia

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by António Polónia. 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 António Polónia. The network helps show where António Polónia may publish in the future.

Co-authorship network of co-authors of António Polónia

This figure shows the co-authorship network connecting the top 25 collaborators of António Polónia. A scholar is included among the top collaborators of António Polónia 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 António Polónia. António Polónia is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Eloy, Catarina, et al.. (2025). Clinical advantages in providing artificial intelligence-assisted prostate cancer diagnosis: A pilot study. Pathology - Research and Practice. 271. 156007–156007.

Polónia, António, et al.. (2024). Human–machine interaction in computational cancer pathology. SHILAP Revista de lepidopterología. 5. 100062–100062. 1 indexed citations

Fonseca-Moutinho, José, et al.. (2024). Somatic Mutations in KEAP1-NRF2 Complex in Breast Cancer. Cancers. 16(13). 2411–2411. 1 indexed citations

Gullo, Irene, Dina Leitão, Carla Oliveíra, et al.. (2024). HER2 and PD-L1 Expression in Gastric and Gastroesophageal Junction Cancer: Insights for Combinatorial Targeting Approaches. Cancers. 16(6). 1227–1227. 4 indexed citations

Shi, Ruoyu, et al.. (2024). Image analysis for bright-field HER2 in situ hybridization: validation for clinical use. Archiv für Pathologische Anatomie und Physiologie und für Klinische Medicin. 486(3). 541–549. 2 indexed citations

Polónia, António, et al.. (2024). Using artificial intelligence to prioritize pathology samples: report of a test drive. Archiv für Pathologische Anatomie und Physiologie und für Klinische Medicin. 487(1). 203–208. 3 indexed citations

Conde‐Sousa, Eduardo, Ming Feng, Kele Xu, et al.. (2022). HEROHE Challenge: Predicting HER2 Status in Breast Cancer from Hematoxylin–Eosin Whole-Slide Imaging. Journal of Imaging. 8(8). 213–213. 25 indexed citations

Polónia, António, et al.. (2022). The spectrum of HER2 expression in breast cancer: linking immunohistochemistry quantification with in situ hybridization assay. Archiv für Pathologische Anatomie und Physiologie und für Klinische Medicin. 480(6). 1171–1179. 6 indexed citations

Pagliuca, Francesca, et al.. (2022). Decline of case reports in pathology and their renewal in the digital age: an analysis of publication trends over four decades. Journal of Clinical Pathology. 76(2). 76–81. 4 indexed citations

10.

Balkenhol, Maschenka, Roberto Salgado, Mark E. Sherman, et al.. (2022). Deep learning for fully-automated nuclear pleomorphism scoring in breast cancer. npj Breast Cancer. 8(1). 120–120. 12 indexed citations

11.

Fraggetta, Filippo, Vincenzo L’Imperio, Sabine Leh, et al.. (2021). Best Practice Recommendations for the Implementation of a Digital Pathology Workflow in the Anatomic Pathology Laboratory by the European Society of Digital and Integrative Pathology (ESDIP). Diagnostics. 11(11). 2167–2167. 69 indexed citations

12.

Santos, Joana Dos, et al.. (2021). Squamous cell carcinoma with sarcomatous transformation of the penis. Autopsy and Case Reports. 11. e2021303–e2021303. 1 indexed citations

13.

Eloy, Catarina, et al.. (2020). HER2 genomic heterogeneity is a frequent event in gastroesophageal adenocarcinoma and correlates with tumor morphology. Pathology - Research and Practice. 216(9). 153090–153090. 1 indexed citations

14.

Polónia, António, et al.. (2020). Digital Versus Optical Diagnosis of Follicular Patterned Thyroid Lesions. Head and Neck Pathology. 15(2). 537–543. 9 indexed citations

15.

Świderska-Chadaj, Żaneta, Hans Pinckaers, Mart van Rijthoven, et al.. (2019). Learning to detect lymphocytes in immunohistochemistry with deep learning. Medical Image Analysis. 58. 101547–101547. 104 indexed citations

16.

Eloy, Catarina, et al.. (2019). What to expect from the 2018 ASCO/CAP HER2 guideline in the reflex in situ hybridization test of immunohistochemically equivocal 2+ cases?. Archiv für Pathologische Anatomie und Physiologie und für Klinische Medicin. 475(3). 303–311. 9 indexed citations

17.

Freitas, Daniela, Diana Campos, Joana Gomes, et al.. (2019). O-glycans truncation modulates gastric cancer cell signaling and transcription leading to a more aggressive phenotype. EBioMedicine. 40. 349–362. 71 indexed citations

18.

Fondón, Irene, Auxiliadora Sarmiento, Á. García, et al.. (2018). Automatic classification of tissue malignancy for breast carcinoma diagnosis. Computers in Biology and Medicine. 96. 41–51. 53 indexed citations

19.

Araújo, Teresa, Guilherme Aresta, Eduardo Castro, et al.. (2017). Classification of breast cancer histology images using Convolutional Neural Networks. PLoS ONE. 12(6). e0177544–e0177544. 648 indexed citations breakdown →

20.

Polónia, António, Regina Pinto, José Cameselle‐Teijeiro, Fernando Schmitt, & Joana Paredes. (2017). Prognostic value of stromal tumour infiltrating lymphocytes and programmed cell death-ligand 1 expression in breast cancer. Journal of Clinical Pathology. 70(10). 860–867. 39 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.

Explore authors with similar magnitude of impact