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Towards Trustworthy AI in Neuro-Oncology: A Systematic Review of Explainable AI Models for Brain Tumor Detection
Journal of Robotics and Control (JRC) · Vol. 6 No. 6 (2025) · hlm. 2697–2714
- ISSN
- 2715-5072, 2715-5056
- Terbit
- 2025-11-11
- Penerbit
- Universitas Muhammadiyah Yogyakarta
- Bahasa
- eng
Abstrak
Artificial intelligence has shown significant potential in brain tumor detection using MRI. Despite high accuracy, most AI models function as “black boxes,” limiting their trust and usability in clinical settings. Explainable AI (XAI) has emerged to address this by improving transparency and interpretability of AI decisions. This systematic review investigates the landscape of XAI models developed for brain tumor detection and provides a structured evaluation of their clinical trustworthiness. The key contribution of this review is a synthesis of current methods, datasets, evaluation strategies, and practical implications, with a focus on how trust is assessed and established. Following PRISMA guidelines, 21 peer-reviewed studies published between 2020 and 2024 were selected. Each study was analyzed in terms of its AI model, dataset characteristics, XAI technique (SHAP, LIME, Grad-CAM), trustworthiness evaluation method, and clinical relevance. The findings reveal a dominant reliance on retrospective datasets (BraTS, Figshare, and institutional MRI repositories) with significant variability in data volume and annotation quality. XAI methods were primarily used for pixel-level saliency, modality attribution, or case-level interpretation, often without standardized validation protocols. Only a few studies involved clinical experts in evaluation, and fewer still reported outcomes like clinician trust or decision confidence. Furthermore, visual interpretability was often qualitative and lacked measurable alignment with expert-defined tumor regions. Uncertainty quantification and cross-institutional generalizability were also rarely addressed. In conclusion, while XAI shows promise in enhancing the trustworthiness of AI-based neuro-oncological tools, future research must prioritize human-centered validation, prospective clinical testing, and standardized evaluation frameworks to enable meaningful clinical translation.
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- Rajamangala University of Technology
- Universiti of Malaysia Sabah
- Institut Teknologi Sepuluh Nopember
- Institut Teknologi Dan Bisnis STIKOM Bali
- Hallym University
- Afiliasi tidak diketahui
- Organisasi berbeda
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Tampilkan sebagai tabel
| Rekan penulis | Organisasi | Artikel bersama |
|---|---|---|
| Muhammad Nur Afnan Uda | Afiliasi tidak diketahui | 6 |
| Uda Hashim | Afiliasi tidak diketahui | 6 |
| Dechrit Maneetham | Rajamangala University of Technology | 5 |
| Evi Triandini | Institut Teknologi Dan Bisnis STIKOM Bali | 5 |
| Agus Riyadi | Afiliasi tidak diketahui | 4 |
| Stralen Pratasik | Afiliasi tidak diketahui | 4 |
| Nipat Jongsawat | Rajamangala University of Technology | 3 |
| Anucha Tungkasthan | Rajamangala University of Technology | 3 |
| Wawan Yunanto | Afiliasi tidak diketahui | 3 |
| Made Krisnanda | Afiliasi tidak diketahui | 3 |
| Abdul Wahid Wahab | Afiliasi tidak diketahui | 2 |
| Hasnah Natsir | Afiliasi tidak diketahui | 2 |
| Umi Kultsum | Afiliasi tidak diketahui | 2 |
| Benchalak Maungmeesri | Afiliasi tidak diketahui | 2 |
| Sasithorn Khonthon | Afiliasi tidak diketahui | 2 |
| Natan Derek | Afiliasi tidak diketahui | 2 |
| Abdul Karim | Hallym University | 1 |
| M. N. A. Uda | Universiti of Malaysia Sabah | 1 |
| U. Hashim | Universiti of Malaysia Sabah | 1 |
| Sahidin Sahidin | Afiliasi tidak diketahui | 1 |
| Idhul Ade Rikit Fitra | Afiliasi tidak diketahui | 1 |
| DIKI KURNIAWAN | Afiliasi tidak diketahui | 1 |
| Febi Adriana Mutiara | Afiliasi tidak diketahui | 1 |
| Mustari Mustari | Afiliasi tidak diketahui | 1 |
| M Maulana Kurnia Pratama | Afiliasi tidak diketahui | 1 |
| Damma Salama | Afiliasi tidak diketahui | 1 |
| Nurwahyuni Ode | Afiliasi tidak diketahui | 1 |
| Firdaus Firdaus | Afiliasi tidak diketahui | 1 |
| Nunuk Hariani Soekamto | Afiliasi tidak diketahui | 1 |
| Fatimah Fatimah | Afiliasi tidak diketahui | 1 |
| Dewi Lidiawati | Afiliasi tidak diketahui | 1 |
| Adriani Adriani | Afiliasi tidak diketahui | 1 |
| Seniwati Dali | Afiliasi tidak diketahui | 1 |
| Sulfiani Sulfiani | Afiliasi tidak diketahui | 1 |
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