Evaluating the Effectiveness of Machine Learning Models for Classifying Chemical Inhibitors: A Case Study of Aromatase Inhibitors and Pubchem's Molecular Fingerprint Descriptors
Inproceedings
عنوان الكتاب :
2023 International Conference on Networking and Advanced Systems (ICNAS)
معلومات
السنة :2023
الصفحات :1-7
التفاصيل
Evaluating the Effectiveness of Machine Learning Models for Classifying Chemical Inhibitors: A Case Study of Aromatase Inhibitors and Pubchem's Molecular Fingerprint Descriptors
A. Abdelkrim, A. Bouramoul, I. Zenbout and S. Brahimi. 2023. Evaluating the Effectiveness of Machine Learning Models for Classifying Chemical Inhibitors: A Case Study of Aromatase Inhibitors and Pubchem's Molecular Fingerprint Descriptors. In Proceedings of the 2023 International Conference on Networking and Advanced Systems (ICNAS), 1-7. DOI: https://doi.org/10.1109/ICNAS59892.2023.10330448.
APA :
Abdelkrim, A., Bouramoul, A., Zenbout, I. & Brahimi, S. (2023). Evaluating the Effectiveness of Machine Learning Models for Classifying Chemical Inhibitors: A Case Study of Aromatase Inhibitors and Pubchem's Molecular Fingerprint Descriptors. In Proceedings of the 2023 International Conference on Networking and Advanced Systems (ICNAS), 1-7. DOI: https://doi.org/10.1109/ICNAS59892.2023.10330448
IEEE :
A. Abdelkrim, A. Bouramoul, I. Zenbout and S. Brahimi, "Evaluating the Effectiveness of Machine Learning Models for Classifying Chemical Inhibitors: A Case Study of Aromatase Inhibitors and Pubchem's Molecular Fingerprint Descriptors". In Proceedings of the 2023 International Conference on Networking and Advanced Systems (ICNAS), pp. 1-7, 2023. DOI: https://doi.org/10.1109/ICNAS59892.2023.10330448.
BibTeX :
@inproceedings{misc-lab-428, author = {Abdelkrim, Ali and Bouramoul, Abdelkrim and Zenbout, Imene and Brahimi, Said}, title = {Evaluating the Effectiveness of Machine Learning Models for Classifying Chemical Inhibitors: A Case Study of Aromatase Inhibitors and Pubchem's Molecular Fingerprint Descriptors}, booktitle = {2023 International Conference on Networking and Advanced Systems (ICNAS)}, pages = {1--7}, year = {2023}, doi = {10.1109/ICNAS59892.2023.10330448}, url = {https://doi.org/10.1109/ICNAS59892.2023.10330448}, keywords = {Logistic regression;Sensitivity;Inhibitors;Biological system modeling;Buildings;Fingerprint recognition;Multilayer perceptrons;Machine Learning;Aromatase;Breast Cancer;QSAR;Pubchem Fingerprints} }
RIS :
TY - CONF TI - Evaluating the Effectiveness of Machine Learning Models for Classifying Chemical Inhibitors: A Case Study of Aromatase Inhibitors and Pubchem's Molecular Fingerprint Descriptors AU - A. Abdelkrim AU - A. Bouramoul AU - I. Zenbout AU - S. Brahimi PY - 2023 BT - 2023 International Conference on Networking and Advanced Systems (ICNAS) SP - 1 EP - 7 KW - Logistic regression;Sensitivity;Inhibitors;Biological system modeling;Buildings;Fingerprint recognition;Multilayer perceptrons;Machine Learning;Aromatase;Breast Cancer;QSAR;Pubchem Fingerprints DO - 10.1109/ICNAS59892.2023.10330448 UR - https://doi.org/10.1109/ICNAS59892.2023.10330448 ID - misc-lab-428 ER -