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    SGTCDA: Prediction of circRNA-drug sensitivity associations with interpretable graph transformers and effective assessment by Hongwei Xia, Caiyue Dong, Xinxing Chen, Zhuoyu Wei, Lichuan Gu, Xiaolei Zhu

    Published 2024-11-01
    “…To address these issues, we propose a strategy to evaluate models based on independent test sets for association prediction-related studies. …”
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    Barlow Twins deep neural network for advanced 1D drug–target interaction prediction by Maximilian G. Schuh, Davide Boldini, Annkathrin I. Bohne, Stephan A. Sieber

    Published 2025-02-01
    “…Furthermore, we advance the field by proposing an influence method that elucidates model decision-making, thereby providing deeper insights into molecular interactions and improving the interpretability of drug-target interactions predictions. …”
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    MFE-DDI: A multi-view feature encoding framework for drug-drug interaction prediction by Lingfeng Wang, Yinghong Li, Yaozheng Zhou, Liping Guo, Congzhou Chen

    Published 2025-01-01
    “…In this study, we propose the Multi-view Feature Embedding for drug-drug interaction prediction (MFE-DDI), which integrates SMILES information, molecular graph data and atom spatial semantic information to model drugs from multiple perspectives and encapsulate the intricate drug information crucial for predicting DDIs. …”
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  14. 11174

    ML-CKDP: Machine learning-based chronic kidney disease prediction with smart web application by Rajib Kumar Halder, Mohammed Nasir Uddin, Md. Ashraf Uddin, Sunil Aryal, Sajeeb Saha, Rakib Hossen, Sabbir Ahmed, Mohammad Abu Tareq Rony, Mosammat Farida Akter

    Published 2024-12-01
    “…Additionally, we present a real-time web-based application to operationalize the model, enhancing accessibility for healthcare practitioners and stakeholders.Web app link: https://rajib-research-kedney-diseases-prediction.onrender.com/…”
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