Large-scale machine-learning-based phenotyping significantly improves genomic discovery for optic nerve head morphology B Alipanahi, F Hormozdiari, B Behsaz, J Cosentino, ZR McCaw, ... The American Journal of Human Genetics 108 (7), 1217-1230, 2021 | 53 | 2021 |
Inference of chronic obstructive pulmonary disease with deep learning on raw spirograms identifies new genetic loci and improves risk models J Cosentino, B Behsaz, B Alipanahi, ZR McCaw, D Hill, TH Schwantes-An, ... Nature Genetics 55 (5), 787-795, 2023 | 38 | 2023 |
On minimum sum of radii and diameters clustering B Behsaz, MR Salavatipour Algorithmica 73 (1), 143-165, 2015 | 27 | 2015 |
On minimum vertex cover of generalized Petersen graphs B Behsaz, P Hatami, ES Mahmoodian arXiv preprint arXiv:1008.3208, 2010 | 27 | 2010 |
Approximation Algorithms for Min-Sum k-Clustering and Balanced k-Median B Behsaz, Z Friggstad, MR Salavatipour, R Sivakumar Algorithmica 81, 1006-1030, 2019 | 18* | 2019 |
New approximation algorithms for the unsplittable capacitated facility location problem B Behsaz, MR Salavatipour, Z Svitkina Algorithmica 75, 53-83, 2016 | 16 | 2016 |
Sos 2004: An attempt towards a multi-agent rescue team SA Amraii, B Behsaz, M Izadi, H Janzadeh, F Molazem, A Rahimi, ... Proc. 8th RoboCup Int’l Symposium, 2004 | 14 | 2004 |
A new learning algorithm for the maxq hierarchical reinforcement learning method F Mirzazadeh, B Behsaz, H Beigy 2007 International Conference on Information and Communication Technology …, 2007 | 12 | 2007 |
Comparison of global computing with grid computing B Behsaz, P Jaferian, MR Meybodi 2006 Seventh International Conference on Parallel and Distributed Computing …, 2006 | 8 | 2006 |
Approximation Algorithms for Minimum-Load k-Facility Location S Ahmadian, B Behsaz, Z Friggstad, A Jorati, MR Salavatipour, C Swamy ACM Transactions on Algorithms (TALG) 14 (2), 1-29, 2018 | 7* | 2018 |
Unsupervised representation learning improves genomic discovery for lung function and respiratory disease prediction T Yun, J Cosentino, B Behsaz, ZR McCaw, D Hill, R Luben, D Lai, J Bates, ... medRxiv, 2023.04. 28.23289285, 2023 | 6* | 2023 |
Predicting cardiovascular disease risk using photoplethysmography and deep learning WH Weng, S Baur, M Daswani, C Chen, L Harrell, S Kakarmath, M Jabara, ... PLOS Global Public Health 4 (6), e0003204, 2024 | 5 | 2024 |
Unsupervised representation learning on high-dimensional clinical data improves genomic discovery and prediction T Yun, J Cosentino, B Behsaz, ZR McCaw, D Hill, R Luben, D Lai, J Bates, ... Nature Genetics 56 (8), 1604-1613, 2024 | 4 | 2024 |
NEFRL: A new neuro-fuzzy system for episodic reinforcement learning tasks B Behsaz, R Safabakhsh 2007 Frontiers in the Convergence of Bioscience and Information Technologies …, 2007 | 3 | 2007 |
Utilizing multimodal AI to improve genetic analyses of cardiovascular traits Y Zhou, J Cosentino, T Yun, MI Biradar, J Shreibati, D Lai, ... medRxiv, 2024 | 2 | 2024 |
Approximation algorithms for clustering problems B Behsaz | 2 | 2012 |
Estimation of Probability Density Function by Dependence Tree Methods for Pattern Recognition Systems B Behsaz, M Rahmati Tech. Rep. U. Alberta, 2006 | 2 | 2006 |
Beyond detection: AI-based classification of breast cancer invasiveness using cell-free orphan non-coding RNAs M Karimzadeh, TB Cavazos, NC Chen, NK Tbeileh, D Siegel, ... Cancer Research 84 (6_Supplement), 3678-3678, 2024 | 1 | 2024 |
USING MACHINE TRANSLATION FOR QUERY REWRITE GENERATION M Ciaramita, A Andryeyev, B Behsaz, S Narayanan, N Gupta, N Houlsby, ... | 1 | 2016 |
Minimizing transmit power consumption in multi-level WSNs for environmental monitoring B Behsaz, MHM MacGregor 2014 IEEE Wireless Communications and Networking Conference (WCNC), 3046-3051, 2014 | 1 | 2014 |