Andaç Batur Çolak

Machine Learning-Based Performance Analysis of Solar Thermal Storage Tanks with Fin-Configured Phase Change Materials

Solar thermal energy storage systems play a vital role in bridging the gap between intermittent solar availability and continuous energy demand; however, their efficiency is severely constrained by the inherently low thermal conductivity of phase change materials. Integrating phy...

A Hybrid and Comparative Machine Learning Framework for Predicting Gestational Diabetes Mellitus via a Prospective Case-Control Design: A Pilot Study Integrating Periodontal Health and Hematological Inflammatory Markers

Background/Objectives: This pilot study aimed to develop and compare advanced machine learning models, specifically a Bayesian-regularized artificial neural network (ANN) and a transformer-enhanced physics-informed neural network (PINN), by integrating periodontal health indices...

Predicting Mortality and the Need for Early Intubation in Intensive Care Patients Using Machine Learning: A Pilot Study

Aim: This pilot study aimed to assess the feasibility and preliminary performance of machine learning models for predicting ICU mortality and the need for intubation within 48 hours using routinely collected admission data.Method: Ten adult intensive care patients were included i...

Boric Acid-Induced Apoptosis in Breast Cancer Subtypes: Comparative Gene Expression and Machine Learning Study

Aim: Breast cancer is a diverse illness that arises from the interplay of outside factors and genetic predisposition. Recently, artificial intelligence approaches have enabled the systematic analysis of potential anticancer agents such as boric acid by modeling the functions of a...