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HISTOLOGY LABORATORY
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" Advancing Laboratory Medicine with AI"Ilias Nikas is an Assistant Professor of Histology at the Medical School, University of Cyprus. He studied Medicine at the University of Thessaloniki, Greece, and performed his doctoral research at the Institute of Pathology, Technical University Munich, Germany. He completed the fellowship program for foreign physicians in the field of Molecular Pathology at the Department of Pathology, Seoul National University, Korea. He also received training in the field of Digital Pathology and Image Analysis at the National Center of Pathology, Vilnius University, Lithuania. Ilias Nikas is a Cytopathologist and a Member of the International Academy of Cytopathology. His research interests focus on the fields of Molecular Pathology and Immunology of Solid Tumors, Molecular Cytopathology, Digital Pathology, and Medical Education related to Histology and Pathology. He also performs systematic reviews and meta-analyses of diagnostic test accuracy studies.
Assistant Professor Ilias Nikas Medical School, University of Cyprus
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Cancer BiomarkersThe aim is to evaluate potential diagnostic, prognostic, and therapeutic biomarkers in various solid malignancies, including the breast, lung, pancreas, urinary bladder, and ovaries. Testing is performed on tissue biopsies or cytologic material (e.g., serous effusions), while each biomarker expression is correlated with various clinicopathological parameters (e.g., tumor grading, staging, response to therapy) and survival in well-characterized patient cohorts. Emerging biomarkers related to the immune microenvironment and response to immunotherapy are also assessed.
Digital Pathology and AI inLaboratory Medicine and Medical EducationThe aim is to advance laboratory medicine, facilitate workflow and enhance precision. Projects include evaluating various diagnostic, prognostic, and predictive cancer biomarkers with the aid of virtual microscopy and AI, testing algorithms that detect neoplasia in clinical samples and using AI as a screening tool in cytologic samples. In medical education, the goal is to integrate AI with histology teaching and assess its effect in student learning outcomes. Applications include the evaluation of histologic slides with AI as a guide, also the creation of active learning tools that help students enhance their microscopy skills and integrate their findings with relevant clinicopathological parameters and radiologic findings.
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Systematic Reviews and Meta-analyses ofDiagnostic Test Accuracy StudiesThe aim is to provide high-quality evidence and improve patient care in the field of laboratory medicine. Projects include evaluating the diagnostic performance of potential or well-established diagnostic biomarkers in tissue or cytology samples and the diagnostic accuracy of various reporting systems.
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SELECTED PUBLICATIONS
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