IMMUNE MEDIATED SIDE EFFECTS OF PEMBROLIZUMAB AND NIVOLUMAB THERAPY: PATHOPHYSIOLOGY, GENETIC CONTRIBUTIONS AND CLINICAL SIGNIFICANCE

Volume 35, Number 7 (2025)

Karamello Halak, Yuseph Mohamed, Armantas Gintautas Abstract Pembrolizumab and nivolumab are examples of immune checkpoint inhibitors (ICIs) drugs that are cancer trea­ting drugs that reactivate antitumor immune responses. But they result in immune related side effects (irAEs) that are typically multisystemic and unpredictable. In additionally referring to advanced artificial intelligence (machine learning) for early detection…

ARTIFICIAL INTELLIGENCE IN CELL ANALYSIS FOR DISEASE IDENTIFICATION

Volume 35, Number 5 (2025)

Tadas Kraujalis, Rūta Degutytė Abstract This paper presents a review of traditional machine learning algorithms and artificial neural networks for identifying cellular morphological features, subcellular structures, changes in cell division, and viability. It also discusses their applications in predicting and diagnosing various diseases. Finally, it addresses the limitations and challenges that still persist in cell…

APPLICATION OF MACHINE LEARNING TECHNIQUES FOR DISTINGUISHING SCHIZOPHRENIA PATIENTS FROM HEALTHY SUBJECTS USING FRONTAL LOBE FUNCTIONS ASSESSMENTS

Volume 33, Number 5 (2023)

Denisas Dankinas, Elzbieta Budginaitė, Sigita Mėlynytė, Aldona Šiurkutė, Kastytis Dapšys Abstract Machine learning (ML) represents a set of artificial in­telligence techniques that can assist in recognition of schizophrenia by classifying a person as belonging to either clinical or healthy subjects group. In the current study, we employed cognitive assessments of frontal lobe functions (the deficit…