| Gene Set Analysis: Challenges, Opportunities, and Future Research F Maleki, K Ovens, DJ Hogan, AJ Kusalik Frontiers in Genetics 11, 654, 2020 | 169 | 2020 |
| Brief history of artificial intelligence N Muthukrishnan, F Maleki, K Ovens, C Reinhold, B Forghani, R Forghani Neuroimaging Clinics of North America 30 (4), 393-399, 2020 | 118 | 2020 |
| Machine learning algorithm validation: from essentials to advanced applications and implications for regulatory certification and deployment F Maleki, N Muthukrishnan, K Ovens, C Reinhold, R Forghani Neuroimaging Clinics 30 (4), 433-445, 2020 | 96 | 2020 |
| Crop lodging prediction from UAV-acquired images of wheat and canola using a DCNN augmented with handcrafted texture features S Mardanisamani, F Maleki, S Hosseinzadeh Kassani, S Rajapaksa, ... Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019 | 63 | 2019 |
| An image encryption system by cellular automata with memory F Maleki, A Mohades, SM Hashemi, ME Shiri 2008 third international conference on availability, reliability and …, 2008 | 58 | 2008 |
| Size matters: how sample size affects the reproducibility and specificity of gene set analysis F Maleki, K Ovens, I McQuillan, AJ Kusalik Human genomics 13, 1-12, 2019 | 53 | 2019 |
| Overview of machine learning part 1: fundamentals and classic approaches F Maleki, K Ovens, K Najafian, B Forghani, C Reinhold, R Forghani Neuroimaging Clinics 30 (4), e17-e32, 2020 | 52 | 2020 |
| Overview of machine learning: part 2: deep learning for medical image analysis WT Le, F Maleki, FP Romero, R Forghani, S Kadoury Neuroimaging Clinics 30 (4), 417-431, 2020 | 44 | 2020 |
| Generalizability of Machine Learning Models: Quantitative Evaluation of Three Methodological Pitfalls F Maleki, K Ovens, R Gupta, C Reinhold, A Spatz, R Forghani Radiology: Artificial Intelligence 5 (1), e220028, 2023 | 29 | 2023 |
| DAPPLE 2: a tool for the homology-based prediction of post-translational modification sites B Trost, F Maleki, A Kusalik, S Napper Journal of Proteome Research 15 (8), 2760-2767, 2016 | 25 | 2016 |
| A Semi-Self-Supervised learning approach for wheat head detection using extremely small number of labeled samples K Najafian, A Ghanbari, I Stavness, L Jin, GH Shirdel, F Maleki Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021 | 18 | 2021 |
| Dual energy computed tomography in head and neck imaging: pushing the envelope T Sananmuang, M Agarwal, F Maleki, N Muthukrishnan, JC Marquez, ... Neuroimaging Clinics 30 (3), 311-323, 2020 | 18 | 2020 |
| Machine learning applications for head and neck imaging F Maleki, WT Le, T Sananmuang, S Kadoury, R Forghani Neuroimaging Clinics 30 (4), 517-529, 2020 | 17 | 2020 |
| Measuring consistency among gene set analysis methods: a systematic study F Maleki, KL Ovens, DJ Hogan, E Rezaei, AM Rosenberg, AJ Kusalik Journal of bioinformatics and computational biology 17 (05), 1940010, 2019 | 16 | 2019 |
| Juxtapose: a gene-embedding approach for comparing co-expression networks K Ovens, F Maleki, BF Eames, I McQuillan BMC bioinformatics 22, 1-26, 2021 | 13 | 2021 |
| Above and beyond age: prediction of major postoperative adverse events in head and neck surgery MA Mascarella, N Muthukrishnan, F Maleki, MJ Kergoat, K Richardson, ... Annals of Otology, Rhinology & Laryngology 131 (7), 697-703, 2022 | 10 | 2022 |
| Importance of sex and gender factors for COVID-19 infection and hospitalisation: a sex-stratified analysis using machine learning in UK Biobank data Z Azizi, Y Shiba, P Alipour, F Maleki, V Raparelli, C Norris, R Forghani, ... BMJ open 12 (5), e050450, 2022 | 9 | 2022 |
| Radiomics as an emerging tool in the management of brain metastases A Nowakowski, Z Lahijanian, V Panet-Raymond, PM Siegel, K Petrecca, ... Neuro-Oncology Advances 4 (1), vdac141, 2022 | 9 | 2022 |
| Site-specific variation in radiomic features of head and neck squamous cell carcinoma and its impact on machine learning models X Liu, F Maleki, N Muthukrishnan, K Ovens, SH Huang, A Pérez-Lara, ... Cancers 13 (15), 3723, 2021 | 9 | 2021 |
| Gene set databases: a fountain of knowledge or a siren call? F Maleki, K Ovens, I McQuillan, E Rezaei, AM Rosenberg, AJ Kusalik Proceedings of the 10th ACM International Conference on Bioinformatics …, 2019 | 9 | 2019 |
Katie OvensUniversity of CalgaryVerified email at ucalgary.ca
