معرفی
Adalberto Claudio Quiros serves as a Lecturer in Artificial Intelligence within the School of Cancer Sciences at the University of Glasgow, where he bridges advanced machine learning techniques with oncological research to transform cancer diagnostics and treatment. His work focuses on developing AI-driven solutions for analyzing histopathological data to improve cancer outcome prediction and therapeutic decision-making across multiple malignancies.
His research program centers on self-supervised learning applied to digital pathology, with core interests including:
- Development of deep learning frameworks for histomorphological pattern discovery
- Predictive modeling of treatment response and cancer progression
- Unsupervised representation learning from unlabeled whole-slide images
- Integration of AI with clinical oncology for precision medicine applications
- Quantitative analysis of tumor microarchitecture and spatial heterogeneity
Analysis of his publication trajectory reveals a concentrated effort in leveraging self-supervised learning to decode histopathological features predictive of clinical outcomes. His recent work demonstrates consistent innovation in applying these techniques across diverse cancers—including cutaneous squamous cell carcinoma, mesothelioma, osteosarcoma, and lung adenocarcinoma—with particular emphasis on identifying morphological biomarkers for recurrence, metastasis, and treatment resistance. This research program shows increasing clinical translatability through collaborations with oncology and pathology departments.
No scientific awards are documented in available materials. Regarding academic mentoring, no student names or advising activities are mentioned in the provided information. Similarly, details about research grants, laboratory infrastructure, or collaborative research teams are not specified in the source content.
