Qureshi, Rizwan

AI in drug discovery and its clinical relevance

Qureshi, R., Irfan, M., Gondal, T. M., Khan, S., Wu, J., Hadi, M. U., Heymach, J., Le, X., Yan, H., & Alam, T. (2023) · Heliyon

Computational Drug Discovery MethodsMachine Learning in Materials Science

Cited by 319

A Comprehensive Systematic Review of YOLO for Medical Object Detection (2018 to 2023)

Ragab, M. G., Abdulkadir, S. J., Muneer, A., Alqushaibi, A., Sumiea, E. H., Qureshi, R., Al-Selwi, S. M., & Alhussian, H. (2024) · IEEE Access

Advanced Neural Network ApplicationsMedical Image Segmentation Techniques

Cited by 306

Artificial Intelligence and Biosensors in Healthcare and its Clinical Relevance: A Review

Qureshi, R., Irfan, M., Ali, H., Khan, A., Ali, S., shah, Z., Gondal, T. M., Sadak, F., Shah, Z., Hadi, M. U., et al. (2023) · IEEE Access

Artificial Intelligence in Healthcare and EducationInternet of Things and AI

Cited by 205

Artificial Intelligence and Biosensors in Healthcare and its Clinical Relevance: A Review

Qureshi, R., Irfan, M., Ali, H., Khan, A., Ali, S., shah, Z., Gondal, T. M., Sadak, F., Shah, Z., Hadi, M. U., et al. (2023) · IEEE Access

Artificial Intelligence in Healthcare and EducationInternet of Things and AI

Cited by 205

Artificial Intelligence and Biosensors in Healthcare and its Clinical Relevance: A Review

Qureshi, R., Irfan, M., Ali, H., Khan, A., Ali, S., shah, Z., Gondal, T. M., Sadak, F., Shah, Z., Hadi, M. U., et al. (2023) · IEEE Access

Artificial Intelligence in Healthcare and EducationInternet of Things and AI

Cited by 205

Predicting benefit from immune checkpoint inhibitors in patients with non-small-cell lung cancer by CT-based ensemble deep learning: a retrospective study

Saad, M. B., Hong, L., Aminu, M., Vokes, N. I., Chen, P., Salehjahromi, M., Qin, K., Sujit, S. J., Lu, X., Young, E., et al. (2023) · The Lancet Digital Health

Radiomics and Machine Learning in Medical ImagingCancer Immunotherapy and Biomarkers

Cited by 121

Multi-Modal LLMs in Agriculture: A Comprehensive Review

Sapkota, R., Qureshi, R., Hassan, S. Z., Shutske, J., Shoman, M., Sajjad, M., Dharejo, F. A., Paudel, A., Li, J., Meng, Z., et al. (2024) · IEEE Transactions on Automation Science and Engineering

Smart Agriculture and AIMultimodal Machine Learning Applications

Cited by 68

Who is Responsible? The Data, Models, Users or Regulations? A Comprehensive Survey on Responsible Generative AI for a Sustainable Future

Raza, S., Qureshi, R., Zahid, A., Muneer, A., Zafar, A., Kamawal, S., Sadak, F., Fioresi, J., Saeed, M., Sapkota, R., et al. (2025) · arXiv

Ethics and Social Impacts of AIExplainable Artificial Intelligence (XAI)

Cited by 5