Relevance: Pathogenic constitutional variants of Tumor Protein 53 (TP53) underlie Li-Fraumeni syndrome and confer susceptibility to several malignancies that may arise at unusually young ages. Breast cancer diagnosed before 31 years is included in the modified Chompret criteria for TP53 testing, irrespective of family...
L. Skvortsova, D. Shaiken, K. Zhumagozhayev et al.· Eurasian Journal of Oncology...· 0 citations
Emotion recognition from electroencephalography (EEG) signals is a central problem in affective computing. This study benchmarks seven classical machine learning models—XGBoost, LightGBM, Random Forest, Support Vector Machine (SVM), K-Nearest Neighbors (KNN), Decision Tree, and Logistic Regression—for multiclass EEG em...
Raiymbek Nurtay, B. Abdikenov, R. Zhulduzbayev et al.· Computation· 0 citations
Automated breast cancer classification from whole-slide images (WSIs) is hampered by the scarcity of expert-annotated patches and the domain variability inherent to multi-institutional datasets. We propose and compare two semi-supervised frameworks for patch-level tumor classification under limited annotation. The firs...
T. Zhaksylyk, Aruzhan Imasheva, B. Abdikenov et al.· Frontiers in Artificial Inte...· 0 citations
Labeled clinical text is scarce in many non-English healthcare settings, limiting the development of robust clinical NLP systems. We tested whether supervision from Spanish mammography reports improved the classification of Russian-language reports from Kazakhstan. The study included 4279 Spanish and 495 Russian report...
Anuar Dosmaganbetov, T. Zhaksylyk, B. Abdikenov· Information· 0 citations
Background: Public breast ultrasound datasets are assembled around lesions. Of eight sources examined here, five contain no normal images, and under leave-one-dataset-out evaluation, the normal class is therefore almost perfectly confounded with the acquisition source: with one site held out, 356 of the 358 normal trai...
B. Abdikenov, Aruzhan Imasheva, Dauren Izdibay et al.· Information· 0 citations
A systematic literature review following the PRISMA guidelines to examine artificial intelligence methods for handwritten text recognition (HTR) and text restoration in low-resource languages and proposes a concrete development roadmap focusing on systematic digitization, expert annotation, transfer learning, and the c...
Zhanibek Balabayev, S. Biloshchytska, Beibit Abdikenov et al.· Information· 0 citations
The findings show that manual transliteration consistently yields the best translation performance, while noisy automatic romanization reduces these gains, and that LLM-based translation can be competitive with, and in some settings outperform, fine-tuned NMT systems, although this advantage comes with lower interpreta...
A. Mansurova, Meruert Bekmukhamedova, Bekarys Baibolat et al.· Electronics· 0 citations
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