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ORCIDAshkan Ebadi
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2020 – today
- 2024
[j15]E. Zhixuan Zeng
, Ashkan Ebadi, Adrian Florea, Alexander Wong:
COVID-Net L2C-ULTRA: An Explainable Linear-Convex Ultrasound Augmentation Learning Framework to Improve COVID-19 Assessment and Monitoring. Sensors 24(5): 1664 (2024)- [i25]Mohammadmahdi Toobaee, Andrea Schiffauerova, Ashkan Ebadi:
Proximity Matters: Analyzing the Role of Geographical Proximity in Shaping AI Research Collaborations. CoRR abs/2406.06662 (2024) - [i24]Neel Patel, Alexander Wong, Ashkan Ebadi:
Empowering Tuberculosis Screening with Explainable Self-Supervised Deep Neural Networks. CoRR abs/2406.13750 (2024) - [i23]Koosha Shirouyeh, Andrea Schiffauerova, Ashkan Ebadi:
Predicting Star Scientists in the Field of Artificial Intelligence: A Machine Learning Approach. CoRR abs/2407.14559 (2024) - [i22]Ashkan Ebadi, Alain Auger, Yvan Gauthier:
WISDOM: An AI-powered framework for emerging research detection using weak signal analysis and advanced topic modeling. CoRR abs/2409.15340 (2024) - 2023
- [j14]Anahita Hajibabaei, Andrea Schiffauerova, Ashkan Ebadi:
Women and key positions in scientific collaboration networks: analyzing central scientists' profiles in the artificial intelligence ecosystem through a gender lens. Scientometrics 128(2): 1219-1240 (2023) - [j13]Jessy Song, Ashkan Ebadi, Adrian Florea, Pengcheng Xi, Stéphane Tremblay, Alexander Wong:
COVID-Net USPro: An Explainable Few-Shot Deep Prototypical Network for COVID-19 Screening Using Point-of-Care Ultrasound. Sensors 23(5): 2621 (2023) - [j12]Kai Ma, Siyuan He, Grant Sinha, Ashkan Ebadi, Adrian Florea, Stéphane Tremblay, Alexander Wong, Pengcheng Xi:
Towards Building a Trustworthy Deep Learning Framework for Medical Image Analysis. Sensors 23(19): 8122 (2023) - [i21]Jessy Song, Ashkan Ebadi, Adrian Florea, Pengcheng Xi, Stéphane Tremblay, Alexander Wong:
COVID-Net USPro: An Open-Source Explainable Few-Shot Deep Prototypical Network to Monitor and Detect COVID-19 Infection from Point-of-Care Ultrasound Images. CoRR abs/2301.01679 (2023) - 2022
- [j11]Anahita Hajibabaei, Andrea Schiffauerova, Ashkan Ebadi:
Gender-specific patterns in the artificial intelligence scientific ecosystem. J. Informetrics 16(2): 101275 (2022) - [j10]Ashkan Ebadi, Alain Auger, Yvan Gauthier:
Detecting emerging technologies and their evolution using deep learning and weak signal analysis. J. Informetrics 16(4): 101344 (2022) - [i20]Hilda Azimi, Jianxing Zhang, Pengcheng Xi, Hala As'ad, Ashkan Ebadi, Stéphane Tremblay, Alexander Wong:
Improving Classification Model Performance on Chest X-Rays through Lung Segmentation. CoRR abs/2202.10971 (2022) - [i19]Ashkan Ebadi, Alain Auger, Yvan Gauthier:
Detecting Emerging Technologies and their Evolution using Deep Learning and Weak Signal Analysis. CoRR abs/2205.05449 (2022) - [i18]Hilda Azimi, Ashkan Ebadi, Jessy Song, Pengcheng Xi, Alexander Wong:
COVID-Net UV: An End-to-End Spatio-Temporal Deep Neural Network Architecture for Automated Diagnosis of COVID-19 Infection from Ultrasound Videos. CoRR abs/2205.08932 (2022) - [i17]Anahita Hajibabaei, Andrea Schiffauerova, Ashkan Ebadi:
Women, artificial intelligence, and key positions in collaboration networks: Towards a more equal scientific ecosystem. CoRR abs/2205.12339 (2022) - [i16]Kai Ma, Pengcheng Xi, Karim Habashy, Ashkan Ebadi, Stéphane Tremblay, Alexander Wong:
Towards Trustworthy Healthcare AI: Attention-Based Feature Learning for COVID-19 Screening With Chest Radiography. CoRR abs/2207.09312 (2022) - [i15]Ashkan Ebadi, Alain Auger, Yvan Gauthier:
On the evolution of research in hypersonics: application of natural language processing and machine learning. CoRR abs/2208.08507 (2022) - [i14]Ali Ghaemmaghami, Andrea Schiffauerova, Ashkan Ebadi:
Detecting Emerging Technologies in Artificial Intelligence Scientific Ecosystem Using an Indicator-based Model. CoRR abs/2211.01348 (2022) - [i13]Kai Ma, Siyuan He, Pengcheng Xi, Ashkan Ebadi, Stéphane Tremblay, Alexander Wong:
A Trustworthy Framework for Medical Image Analysis with Deep Learning. CoRR abs/2212.02764 (2022) - 2021
- [j9]Ashkan Ebadi, Pengcheng Xi, Stéphane Tremblay, Bruce Spencer, Raman Pall, Alexander Wong:
Understanding the temporal evolution of COVID-19 research through machine learning and natural language processing. Scientometrics 126(1): 725-739 (2021) - [c5]Alexander MacLean, Saad Abbasi, Ashkan Ebadi, Andy Zhao, Maya Pavlova, Hayden Gunraj, Pengcheng Xi, Sonny Kohli, Alexander Wong:
COVID-Net US: A Tailored, Highly Efficient, Self-attention Deep Convolutional Neural Network Design for Detection of COVID-19 Patient Cases from Point-of-Care Ultrasound Imaging. DART/FAIR@MICCAI 2021: 191-202 - [i12]Ashkan Ebadi, Pengcheng Xi, Alexander MacLean, Stéphane Tremblay, Sonny Kohli, Alexander Wong:
COVIDx-US - An open-access benchmark dataset of ultrasound imaging data for AI-driven COVID-19 analytics. CoRR abs/2103.10003 (2021) - [i11]Jianxing Zhang, Pengcheng Xi, Ashkan Ebadi, Hilda Azimi, Stéphane Tremblay, Alexander Wong:
COVID-19 Detection from Chest X-ray Images using Imprinted Weights Approach. CoRR abs/2105.01710 (2021) - [i10]Anahita Hajibabaei, Andrea Schiffauerova, Ashkan Ebadi:
Gender-Specific Patterns in the Artificial Intelligence Scientific Ecosystem. CoRR abs/2106.01446 (2021) - [i9]Elva Luz Crespo Neira, Ashkan Ebadi, Catherine Beaudry, Andrea Schiffauerova:
Influence of cognitive, geographical, and collaborative proximity on knowledge production of Canadian nanotechnology. CoRR abs/2106.02110 (2021) - [i8]Alexander MacLean, Saad Abbasi, Ashkan Ebadi, Andy Zhao, Maya Pavlova, Hayden Gunraj, Pengcheng Xi, Sonny Kohli, Alexander Wong:
COVID-Net US: A Tailored, Highly Efficient, Self-Attention Deep Convolutional Neural Network Design for Detection of COVID-19 Patient Cases from Point-of-care Ultrasound Imaging. CoRR abs/2108.03131 (2021) - [i7]Ashkan Ebadi, Patrick Paul, Sofia Auer, Stéphane Tremblay:
NRC-GAMMA: Introducing a Novel Large Gas Meter Image Dataset. CoRR abs/2111.06827 (2021) - [i6]Siyuan He, Pengcheng Xi, Ashkan Ebadi, Stéphane Tremblay, Alexander Wong:
Performance or Trust? Why Not Both. Deep AUC Maximization with Self-Supervised Learning for COVID-19 Chest X-ray Classifications. CoRR abs/2112.08363 (2021) - 2020
- [j8]Ashkan Ebadi, Stéphane Tremblay, Cyril Goutte, Andrea Schiffauerova:
Application of machine learning techniques to assess the trends and alignment of the funded research output. J. Informetrics 14(2): 101018 (2020) - [i5]Ashkan Ebadi, Pengcheng Xi, Stéphane Tremblay, Bruce Spencer, Raman Pall, Alexander Wong:
Understanding the temporal evolution of COVID-19 research through machine learning and natural language processing. CoRR abs/2007.11604 (2020)
2010 – 2019
- 2019
- [j7]Ashkan Ebadi, Patrick James Tighe, Lei Zhang, Parisa Rashidi:
A quest for the structure of intra- and postoperative surgical team networks: does the small-world property evolve over time? Soc. Netw. Anal. Min. 9(1): 7:1-7:20 (2019) - [c4]Ashkan Ebadi, Yvan Gauthier, Stéphane Tremblay, Patrick Paul:
How can Automated Machine Learning Help Business Data Science Teams? ICMLA 2019: 1186-1191 - 2018
- [i4]Benjamin Shickel, Tyler J. Loftus, Tezcan Ozrazgat-Baslanti, Ashkan Ebadi, Azra Bihorac, Parisa Rashidi:
DeepSOFA: A Real-Time Continuous Acuity Score Framework using Deep Learning. CoRR abs/1802.10238 (2018) - [i3]Ashkan Ebadi, Patrick James Tighe, Lei Zheng, Parisa Rashidi:
A Quest for the Structure of Intra- and Postoperative Surgical Team Networks: Does the Small World Property Evolve over Time? CoRR abs/1803.03359 (2018) - [i2]Lasith Adhikari, Tezcan Ozrazgat-Baslanti, Paul Thottakkara, Ashkan Ebadi, Amir Motaei, Parisa Rashidi, Xiaolin Li, Azra Bihorac:
Improved Predictive Models for Acute Kidney Injury with IDEAs: Intraoperative Data Embedded Analytics. CoRR abs/1805.05452 (2018) - [i1]Ashkan Ebadi, Patrick James Tighe, Lei Zhang, Parisa Rashidi:
Does the Position of Surgical Service Providers in Intra-Operative Networks Matter? Analyzing the Impact of Influencing Factors on Patients' Outcome. CoRR abs/1812.07129 (2018) - 2017
- [j6]Ashkan Ebadi, Patrick James Tighe, Lei Zhang, Parisa Rashidi:
DisTeam: A decision support tool for surgical team selection. Artif. Intell. Medicine 76: 16-26 (2017) - [c3]Anis Davoudi, Tezcan Ozrazgat-Baslanti, Ashkan Ebadi, Alberto C. Bursian, Azra Bihorac, Parisa Rashidi:
Delirium Prediction using Machine Learning Models on Predictive Electronic Health Records Data. BIBE 2017: 568-573 - 2016
- [j5]Ashkan Ebadi, Andrea Schiffauerova:
How to boost scientific production? A statistical analysis of research funding and other influencing factors. Scientometrics 106(3): 1093-1116 (2016) - [j4]Ashkan Ebadi, Andrea Schiffauerova:
iSEER: an intelligent automatic computer system for scientific evaluation of researchers. Scientometrics 107(2): 477-498 (2016) - [c2]Benjamin Shickel, Martin Heesacker, Sherry Benton, Ashkan Ebadi, Paul Nickerson, Parisa Rashidi:
Self-Reflective Sentiment Analysis. CLPsych@HLT-NAACL 2016: 23-32 - 2015
- [j3]Ashkan Ebadi, Andrea Schiffauerova:
How to become an important player in scientific collaboration networks? J. Informetrics 9(4): 809-825 (2015) - [c1]Ashkan Ebadi, Andrea Schiffauerova:
A Computer System for Automatic Evaluation of Researchers' Performance. ISSI 2015 - 2013
- [j2]Ashkan Ebadi, Andrea Schiffauerova:
Impact of Funding on Scientific Output and Collaboration: A Survey of Literature. J. Inf. Knowl. Manag. 12(4) (2013) - [j1]Hamidreza Eslami, Ashkan Ebadi, Andrea Schiffauerova:
Effect of collaboration network structure on knowledge creation and technological performance: the case of biotechnology in Canada. Scientometrics 97(1): 99-119 (2013)
Coauthor Index
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last updated on 2024-10-16 21:22 CEST by the dblp team
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