Artificial Intelligence(AI); Trustworthy AI (TAI); eXplainable AI (XAI); autonomous vehicles, Healthcare, IoT

Chamola, Vinay, Hassija, Vikas, Sulthana Abdul Kareem, Razia ORCID: 0000-0001-5331-1310 , Ghosh, Debshishu, Dhingra, Divyansh and Sikdar, Biplab (2023) A review of trustworthy and eXplainable Artificial Intelligence (XAI). IEEE Access, 11. 78994 -79015. ISSN 2169-3536 (Online) (doi:https://doi.org/10.1109/ACCESS.2023.3294569)

Naive Bayes; decision trees; random forest; K-Nearest neighbours; backpropagation; DBScan, customer relationship management

A, Razia Sulthana ORCID: 0000-0001-5331-1310 , Jaiswal, Anukriti, P, Supraja and L, SaiRamesh (2023) Customer segmentation using machine learning. In: 2023 Third International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies (ICAECT). IEEE, Piscataway, New Jersey. ISBN 978-1665494014 (doi:https://doi.org/10.1109/ICAECT57570.2023.10117924)

heart disease; data mining; naive Bayes; decision trees; prediction

A, Razia Sulthana ORCID: 0000-0001-5331-1310 , A K, Jaithunbi and P, Supraja (2023) Application of machine learning algorithms in predicting the heart disease in patients. In: 2023 Third International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies (ICAECT). IEEE, Piscataway, New Jersey. ISBN 9781665494014 (doi:https://doi.org/10.1109/ICAECT57570.2023.10117653)

machine learning, biomedical image segmentation, brain tumours, convolutional neural networks

Ilango, Dhakshina and Sulthana, Razia ORCID: 0000-0001-5331-1310 (2023) Segmentation of brain tumours from MRI images using CNN. In: Inventive Systems and Control Proceedings of ICISC 2023. Lecture Notes in Networks and Systems, 672 . Springer, pp. 693-706. ISBN 9789819916238 ISSN 2367-3370 (Print), 2367-3389 (Online) (doi:https://doi.org/10.1007/978-981-99-1624-5_51)

security breach, Naive bayes, logistic regression, machine learning

Sulthana, Razia ORCID: 0000-0001-5331-1310 , Verma, Avani and Jaithunbi, A. K. (2023) A detailed analysis on spam emails and detection using machine learning algorithms. In: Inventive Systems and Control Proceedings of ICISC 2023. Lecture Notes in Networks and Systems, 672 . Springer, pp. 65-76. ISBN 9789819916238 ISSN 2367-3370 (Print), 2367-3389 (Online) (doi:https://doi.org/10.1007/978-981-99-1624-5_5)