The Application of AI in Oncology Research in Türkiye: Impact and Future Directions

Artificial Intelligence (AI) techniques such as machine learning and deep learning have seen increasing application in medical diagnosis. The field of oncology has seen the application of AI in cancer detection and diagnosis, treatment selection and survival prediction for patients. This study evaluates recent research in the application of AI in oncology and its potential impact on the Turkish health and medical sectors through a review-based study. We identified 41 research studies from 2020 to 2024 applying AI in oncology utilizing datasets curated from Turkish medical data. Our analysis showed that all studies were retrospective, with the majority being diagnosis studies. Patient datasets were unicentric, relatively small and not publicly available. Thus, most of the reported results cannot be generalized until the models are validated in larger, more diverse studies. The majority of studies concentrated on model accuracy, with limited evidence of model integration in clinical settings or within the health industry. Our findings indicate that more work is required in order to develop more advanced approaches for human-AI collaboration, i.e., clinician–in-the-loop or patient-in-the-loop approaches. An important step toward achieving this is to create and maintain a national dataset for AI in oncology research in Türkiye. Although this study is specific to Türkiye, we anticipate that its findings may be relevant to countries with similar research environments.

Authors

Institutions

Publication Details

Journal
Gazi University Journal of Science Part A Engineering and Innovation
Published
2025-09-30
DOI
https://doi.org/10.54287/gujsa.1768020
Citations
2
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
article
Field-Weighted Citation Impact
2.72
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

The Application of AI in Oncology Research in Türkiye: Impact and Future Directions

Rasha Osman, Hilal Arslan
2 citations
Gazi University Journal of Science Part A Engineering and Innovation
Radiomics and Machine Learning in Medical Imaging
2.72
article

The Application of AI in Oncology Research in Türkiye: Impact and Future Directions

Rasha Osman, Hilal Arslan
article en
2 citations

Abstract

Artificial Intelligence (AI) techniques such as machine learning and deep learning have seen increasing application in medical diagnosis. The field of oncology has seen the application of AI in cancer detection and diagnosis, treatment selection and survival prediction for patients. This study evaluates recent research in the application of AI in oncology and its potential impact on the Turkish health and medical sectors through a review-based study. We identified 41 research studies from 2020 to 2024 applying AI in oncology utilizing datasets curated from Turkish medical data. Our analysis showed that all studies were retrospective, with the majority being diagnosis studies. Patient datasets were unicentric, relatively small and not publicly available. Thus, most of the reported results cannot be generalized until the models are validated in larger, more diverse studies. The majority of studies concentrated on model accuracy, with limited evidence of model integration in clinical settings or within the health industry. Our findings indicate that more work is required in order to develop more advanced approaches for human-AI collaboration, i.e., clinician–in-the-loop or patient-in-the-loop approaches. An important step toward achieving this is to create and maintain a national dataset for AI in oncology research in Türkiye. Although this study is specific to Türkiye, we anticipate that its findings may be relevant to countries with similar research environments.

Gazi University Journal of Science Part A Engineering and InnovationVol. 12(3)
Ankara Yıldırım Beyazıt University (TR)
Openalex Percentile: Top 9%
Radiomics and Machine Learning in Medical Imaging
2.72
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

The Application of AI in Oncology Research in Türkiye: Impact and Future Directions — Rasha Osman, Hilal Arslan · Gazi University Journal of Science Part A Engineering and Innovation (2025) | TGRS Research Map | TGRS