** Funder: Deputyship for Research & Innovation, Ministry of Education in Saudi Arabia

Abdul Kareem, Razia Sulthana ORCID: https://orcid.org/0000-0001-5331-1310, Chamola, Vinay, Hussain, Amir, Hussain, Zain and Albalwy, Faisal ORCID: https://orcid.org/0000-0002-2342-2156 (2023) A novel end-to-end deep convolutional neural network based skin lesion classification framework. Expert Systems with Applications, 246:123056. pp. 1-19. ISSN 0957-4174 (Print), 1873-6793 (Online) (doi:10.1016/j.eswa.2023.123056)

10.13039/501100001459-Ministry of Education, Singapore (Grant Number: A-0009040-00-00 and A-0009040-01-00)

Chamola, Vinay, Hassija, Vikas, Sulthana Abdul Kareem, Razia ORCID: https://orcid.org/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:10.1109/ACCESS.2023.3294569)

Deputyship for Research & Innovation, Ministry of Education in Saudi Arabia (Project No. 445-9-512)

A., Razia Sulthana ORCID: https://orcid.org/0000-0001-5331-1310, Chamola, Vinay, Hussain, Amir, Hussain, Zain and Albalwy, Faisal (2023) A novel end-to-end deep convolutional neural network based skin lesion classification framework. Expert system with applications. ISSN 0957-4174 (Print), 1873-6793 (Online) (doi:10.1016/j.eswa.2023.123056)

EP/W006308/1

Stoyanov, Stoyan ORCID: https://orcid.org/0000-0001-6091-1226, Sulthana, Razia ORCID: https://orcid.org/0000-0001-5331-1310, Tilford, Tim ORCID: https://orcid.org/0000-0001-8307-6403, Zhang, Xiaotian, Hu, Yihua, Yang, Xingyu, Shen, Yaochun and Wang, Yangang (2025) Modelling the fatigue damage in power components using machine learning technology. Power Electronic Devices and Components, 10:100079. ISSN 2772-3704 (Online) (doi:10.1016/j.pedc.2025.100079)

EP/W006405/1

Stoyanov, Stoyan ORCID: https://orcid.org/0000-0001-6091-1226, Sulthana, Razia ORCID: https://orcid.org/0000-0001-5331-1310, Tilford, Tim ORCID: https://orcid.org/0000-0001-8307-6403, Zhang, Xiaotian, Hu, Yihua, Yang, Xingyu, Shen, Yaochun and Wang, Yangang (2025) Modelling the fatigue damage in power components using machine learning technology. Power Electronic Devices and Components, 10:100079. ISSN 2772-3704 (Online) (doi:10.1016/j.pedc.2025.100079)

EP/W006642/ 1

Stoyanov, Stoyan ORCID: https://orcid.org/0000-0001-6091-1226, Sulthana, Razia ORCID: https://orcid.org/0000-0001-5331-1310, Tilford, Tim ORCID: https://orcid.org/0000-0001-8307-6403, Zhang, Xiaotian, Hu, Yihua, Yang, Xingyu, Shen, Yaochun and Wang, Yangang (2025) Modelling the fatigue damage in power components using machine learning technology. Power Electronic Devices and Components, 10:100079. ISSN 2772-3704 (Online) (doi:10.1016/j.pedc.2025.100079)

EP/X024377/1

Stoyanov, Stoyan ORCID: https://orcid.org/0000-0001-6091-1226, Sulthana, Razia ORCID: https://orcid.org/0000-0001-5331-1310, Tilford, Tim ORCID: https://orcid.org/0000-0001-8307-6403, Zhang, Xiaotian, Hu, Yihua, Yang, Xingyu, Shen, Yaochun and Wang, Yangang (2025) Modelling the fatigue damage in power components using machine learning technology. Power Electronic Devices and Components, 10:100079. ISSN 2772-3704 (Online) (doi:10.1016/j.pedc.2025.100079)

UK Engineering and Physical Sciences Research Council (EPSRC) - Grants Ref. EP/M026981/1, EP/T021063/1, EP/T024917/1

Abdul Kareem, Razia Sulthana ORCID: https://orcid.org/0000-0001-5331-1310, Chamola, Vinay, Hussain, Amir, Hussain, Zain and Albalwy, Faisal ORCID: https://orcid.org/0000-0002-2342-2156 (2023) A novel end-to-end deep convolutional neural network based skin lesion classification framework. Expert Systems with Applications, 246:123056. pp. 1-19. ISSN 0957-4174 (Print), 1873-6793 (Online) (doi:10.1016/j.eswa.2023.123056)