An integrated SHAP-MCDM approach for slope stability prediction based on machine learning algorithms
Demir, Alparslan Serhat | Dağdeviren, Uğur | Kurnaz, Talas Fikret | Erden, Caner | Kökçam, Abdullah Hulusi
In machine learning (ML)-based slope stability prediction studies, feature importance results often vary across different algorithms, leading to inconsistent interpretations. This issue arises because the importance of features differs depending on the algorithm applied within the same study. To address this challenge, this study proposes a novel methodology for obtaining a final, unified ranking of features by combining the feature importance rankings of various ML algorithms using a Multi-Criteria Decision-Making (MCDM) technique. This approach ensures a consistent and reliable feature ranking derived from the results of successful ML models. Furthermore, the study demonstrates how performance indicators of ML algorithms can be translated into criterion weights within the MCDM f...
The impact of language differences on the readability, quality, and reliability of information provided by artificial intelligence chatbots regarding vital pulp therapy: a cross-sectional study
Şimşek, Emine
Background: The increasing use of artificial intelligence (AI) chatbots in healthcare has highlighted the need to evaluate the accuracy, reliability, and readability of the clinical information they provide. Vital pulp therapy is one of the fundamental biological approaches in modern dentistry aimed at preserving pulp vitality, and the quality of information related to this topic is highly important for clinical decision-making. The present study aimed to assess whether the readability, quality, and reliability of information provided by six different AI-based chatbots (ChatGPT, ChatGPT-4o, Gemini, Microsoft Copilot, Perplexity, and Claude) regarding vital pulp therapy vary depending on language differences. Methods: After a comprehensive literature review, 12 questions related to vital pu...
A new species of Ochridacyclops (Kiefer, 1937) (Copepoda, Cyclopoida) from Japan
KARAYTUĞ SUPHAN
A new species of cyclopoid copepod, Ochridacyclops nipponensis is described from Japan. This is the third species of the genus. The type material was collected from small streams in the mountainous regions in Shikoku. The new species can easily be distinguished from other members of genus by its 12-segmented antennule, by the proportional length of genital double-somite relative to the length of 3 free abdominal somites, and by the shape of caudal rami. The male is unknown.
Nanosponge-based strategies against antimicrobial resistance: investigating the antimicrobial and antibiofilm activity of drug-free nanosponges
ÇOBANOĞLU ECE | GÜR Çiğdem | ÖKSÜZ ZEHRA | Uluca Han Bahar | ŞAHİN NEFİSE ÖZLEN | SERİN MEHMET SAMİ
Antimicrobial resistance is a critical global health concern, necessitating innovative therapeutic strategies. Nanosponges, porous and biocompatible nanostructures, are widely used to enhance antimicrobial agent efficacy, yet their direct antimicrobial potential in drug-free formulations remains largely unexplored. This study investigates the antimicrobial and antibiofilm properties of drug-free nanosponges synthesized via emulsion solvent evaporation and solvent methods. Nanosponges were tested against ten clinically relevant pathogens as well as their ability to inhibit biofilm formation and eradicate preformed biofilms in Staphylococcus aureus (MRSA). The drug-free nanosponges exhibited low-to-moderate antimicrobial activity against the common pathogens assessed in this study, while al...
Explainable AI using ensemble machine learning with integrated SHapley additive explanations (SHAP)-Borda approach for estimation of the safety factor against soil liquefaction
Dağdeviren, Uğur | Demir, Alparslan Serhat | Erden, Caner | Kökçam, Abdullah Hulusi | Kurnaz, Talas Fikret
In most of the studies on soil liquefaction prediction based on Machine Learning (ML), the models presented are presented in a closed box structure. In the studies where the effect of the features on the model performance is analyzed with Interpretability methods, it is seen that the order of effect of the features changes for each ML algorithm. This situation makes the results of the studies conducted on the same subject inconsistent. In this study, we propose an integrated SHapley Additive exPlanations (SHAP)-Borda approach to overcome this problem. With this study, we provide decision makers with ease in explaining ML models by combining SHAP analysis results with the Borda method for the first time. In the study, ensemble ML algorithms were used for soil liquefaction prediction u...