| Gene selection for microarray cancer classification using a new evolutionary method employing artificial intelligence concepts M Dashtban, M Balafar Genomics 109 (2), 91-107, 2017 | 173 | 2017 |
| Gene selection for tumor classification using a novel bio-inspired multi-objective approach M Dashtban, M Balafar, P Suravajhala Genomics 110 (1), 10-17, 2018 | 106 | 2018 |
| A novel approach for vehicle license plate localization and recognition MH Dashtban, Z Dashtban, H Bevrani International Journal of Computer Applications 26 (11), 22-30, 2011 | 59 | 2011 |
| A retrospective cohort study predicting and validating impact of the COVID-19 pandemic in individuals with chronic kidney disease A Dashtban, MA Mizani, S Denaxas, D Nitsch, J Quint, R Corbett, ... Kidney international 102 (3), 652-660, 2022 | 31 | 2022 |
| Identifying subtypes of heart failure from three electronic health record sources with machine learning: an external, prognostic, and genetic validation study A Banerjee, A Dashtban, S Chen, L Pasea, JH Thygesen, G Fatemifar, ... The Lancet Digital Health 5 (6), e370-e379, 2023 | 28 | 2023 |
| Predicting non-attendance in hospital outpatient appointments using deep learning approach M Dashtban, W Li Health Systems 11 (3), 189-210, 2022 | 20 | 2022 |
| Deep learning for predicting non-attendance in hospital outpatient appointments M Dashtban, W Li | 15 | 2019 |
| Identifying subtypes of chronic kidney disease with machine learning: development, internal validation and prognostic validation using linked electronic health records in 350 … A Dashtban, MA Mizani, L Pasea, S Denaxas, R Corbett, JB Mamza, ... EBioMedicine 89, 2023 | 11 | 2023 |
| Risk factors, outcomes and healthcare utilisation in individuals with multimorbidity including heart failure, chronic kidney disease and type 2 diabetes mellitus: a national … L Pasea, A Dashtban, M Mizani, A Bhuva, T Morris, JB Mamza, ... Open Heart 10 (2), e002332, 2023 | 10 | 2023 |
| Design and implementation of super-heterodyne nano-metrology circuits S Olyaee, Z Dashtban, MH Dashtban Frontiers of Optoelectronics 6, 318-326, 2013 | 10 | 2013 |
| Predicting risk of hospital readmission for comorbidity patients through a novel deep learning framework M Dashtban, W Li | 9 | 2020 |
| Using national electronic health records for pandemic preparedness: validation of a parsimonious model for predicting excess deaths among those with COVID-19–a data-driven … MA Mizani, A Dashtban, L Pasea, AG Lai, J Thygesen, C Tomlinson, ... Journal of the Royal Society of Medicine 116 (1), 10-20, 2023 | 7 | 2023 |
| AZD1222 effectiveness against severe COVID-19 in individuals with comorbidity or frailty: The RAVEN cohort study W Meeraus, M Joy, M Ouwens, KS Taylor, S Venkatesan, J Dennis, ... Journal of Infection 88 (4), 106129, 2024 | 6 | 2024 |
| Identifying subtypes of heart failure with machine learning: external, prognostic and genetic validation in three electronic health record sources with 320,863 individuals A Banerjee, S Chen, M Dashtban, L Pasea, JH Thygesen, G Fatemifar, ... medRxiv, 2022.06. 27.22276961, 2022 | 5 | 2022 |
| A novel and robust approach for iris segmentation M Dashtban, P Moradi International Journal of Computer Applications 34 (6), 63-70, 2011 | 5 | 2011 |
| Healthcare Utilisation of 282,080 Individuals with Long COVID Over Two Years: A Multiple Matched Control Cohort Analysis Y Mu, A Dashtban, MA Mizani, C Tomlinson, M Mohamed, M Ashworth, ... | 3 | 2023 |
| Healthcare utilisation of 282,080 individuals with long COVID over two years: a multiple matched control, longitudinal cohort analysis Y Mu, A Dashtban, MA Mizani, C Tomlinson, M Mohamed, M Ashworth, ... Journal of the Royal Society of Medicine 117 (11), 369-381, 2024 | 2 | 2024 |
| Predicting and validating risk of pre-pandemic and excess mortality in individuals with chronic kidney disease A Dashtban, MA Mizani, S Denaxas, D Nitsch, J Quint, R Corbett, ... | 2 | 2021 |
| Vaccinations, cardiovascular drugs, hospitalization, and mortality in COVID-19 and Long COVID A Dashtban, MA Mizani, L Pasea, C Tomlinson, Y Mu, N Islam, S Rafferty, ... International Journal of Infectious Diseases 146, 107155, 2024 | 1 | 2024 |
| Identifying subtypes of type 2 diabetes mellitus with machine learning: development, internal validation, prognostic validation and medication burden in linked electronic … MA Mizani, A Dashtban, L Pasea, Q Zeng, K Khunti, J Valabhji, JB Mamza, ... BMJ Open Diabetes Research and Care 12 (3), e004191, 2024 | 1 | 2024 |
Mohammad Ali Balafarprof of IT University of TabrizE-mail megerősítve itt: tabrizu.ac.ir