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Sponsored AI Networking Cookbook: Practical recipes for AI-assisted network automation and development AI Networking Cookbook: Practical recipes for AI-assisted network automation and development

Author

Z. Kucukakcali

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Open access Oct 2026

Potential Dual Targeting of EGFR and VEGFR2 by Repurposed Drugs for Cholangiocarcinoma: A Molecular Docking Study

Objective: Cholangiocarcinoma is an aggressive hepatobiliary malignancy characterized by high mortality, late-stage diagnosis, and limited systemic treatment options. The epidermal growth factor receptor (EGFR) and vascular endothelial growth factor receptor 2 (VEGFR2) signaling pathways play central roles in tumor cel...

İpek Balıkçı Çiçek, Z. Kucukakcali · 0 citations
#protein folding Open access Oct 2026

Identification of AURKA as a Key Target in Hepatocellular Carcinoma: Integrated Bioinformatics Analysis and Evaluation of Natural Compounds via Molecular Docking

Objective: This study aimed to identify a central molecular target associated with hepatocellular carcinoma (HCC) using bioinformatic methods and to comparatively evaluate the binding potential of reference inhibitors and natural compounds against this target by molecular docking.Materials and Methods: In the GSE76427...

Z. Kucukakcali, İpek Balıkçı Çiçek · 0 citations
Open access Sep 2026

Tree-Based Classification of COVID-19 Using NanoString Whole-Blood Immune-Response Profiles: Comparison of Full-Dataset and LOOCV-Embedded Feature Selection

This exploratory analysis showed that targeted NanoString immune-response profiles contained a compact transcriptomic signal capable of distinguishing COVID-19 from healthy-control measurements within the analyzed dataset, providing proof-of-concept evidence of internal measurement-level discrimination.

Z. Yilmaz, Z. Kucukakcali, Sami Akbulut · 0 citations
Open access 2026

Beyond Binary Classification: A Comprehensive Survival Analysis and Calibration Assessment of the Heart Failure Clinical Records Datase

Background: The Heart Failure Clinical Records dataset (n = 299) is among the most extensively reused benchmark datasets in clinical machine learning, yet the overwhelming majority of published analyses treat patient mortality as a static binary classification target and rarely test the statistical assumptions underlyi...

I. Cicek, Z. Kucukakcali · 0 citations
Open access Sep 2026

Tree-Based Machine Learning for Diagnostic Classification of Dengue Fever Using Routine Hematological Parameters: A Secondary Analysis of a Publicly Available Dataset

Tree-based machine-learning models for dengue classification showed moderate discrimination, with high sensitivity but limited specificity, and yielded numerically higher AUROCs and lower Brier scores than the primary SMOTE-trained LR within this internal-validation framework.

Z. Yilmaz, Z. Kucukakcali, Sami Akbulut · 0 citations
Open access 2026

An Interpretable XGBoost Model for Diabetes Prediction: Nested Cross-Validation, Calibration, and SHAP Analysis

Under a leakage-controlled, unbiased evaluation, XGBoost provided moderate but trustworthy discrimination together with well-calibrated probabilities for diabetes prediction, while SHAP confirmed clinically plausible predictors.

Z. Kucukakcali, I. Cicek · 0 citations

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