Görkem Polat

405 citations
6 papers · 41 · h-index 4

Impact in

Papers in

Görkem Polat

5 papers receiving 40 citations

Peers

Görkem Polat
Comparison fields: 5 of 20
  • Health Informatics 2
  • Gastroenterology 4
  • Computer Science Applications 3
  • Oncology 11
  • Artificial Intelligence 13
Replace Jacob J.S. Alvarez with:
Jacob J.S. Alvarez Singapore
Rebecca A. Deek United States
Yuefeng He China
Quentin Angermann France
Mateo Torres Paraguay
Haythem Ali United States
Davide Placido Denmark
Lê Duy Huỳnh France
Brandon White United States
Nicholas Lucarelli United States
Görkem Polat relative to Jacob J.S. Alvarez Singapore Jacob J.S. Alvarez's profile →
Citations per field
00.5×1.5×2.5×
Jacob J.S. Alvarez · 1×
Citations per year

Countries citing papers authored by Görkem Polat

Since Specialization
Citations

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

Fields of papers citing papers by Görkem Polat

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 6 scholars most cited alongside Görkem Polat, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Görkem Polat Line = papers co-authored together Görkem Polat links everyone, so they are left out of the graph.

All Works

6 of 6 papers shown
#Work
1 202224
2 20229
3 20254
4
Endoscopic Artefact Detection with Ensemble of Deep Neural Networks and False Positive Elimination.
20203
5
Polyp Detection in Colonoscopy Images using Deep Learning and Bootstrap Aggregation
20211
6 20230

About Görkem Polat

Görkem Polat is a scholar working on Computer Vision and Pattern Recognition, Oncology, Artificial Intelligence, Radiology, Nuclear Medicine and Imaging and Pulmonary and Respiratory Medicine, having authored 6 papers that have together received 41 indexed citations. Recurring topics across this work include Colorectal Cancer Screening and Detection (2 papers), Radiomics and Machine Learning in Medical Imaging (1 paper), Currency Recognition and Detection (1 paper), Privacy-Preserving Technologies in Data (1 paper), Domain Adaptation and Few-Shot Learning (1 paper), Digital Imaging for Blood Diseases (1 paper), Adversarial Robustness in Machine Learning (1 paper) and Remote-Sensing Image Classification (1 paper). The work is most often cited by research in Health Informatics (2 citations), Gastroenterology (4 citations), Computer Science Applications (3 citations), Oncology (11 citations) and Artificial Intelligence (13 citations). Görkem Polat has collaborated with scholars based in Türkiye. Frequent co-authors include Alptekin Temizel, Özlen Atuğ, Yeşim Özen Alahdab, Haluk Tarık Kani, Altan Koçyiğit and Kerem Kayabay. Their work appears in journals such as Inflammatory Bowel Diseases, Future Generation Computer Systems, Expert Systems with Applications and OpenMETU (Middle East Technical University).

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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