Transdeeplab: Convolution-free transformer-based deeplab v3+ for medical image segmentation R Azad, M Heidari, M Shariatnia, EK Aghdam, S Karimijafarbigloo, E Adeli, ... International Workshop on PRedictive Intelligence In MEdicine, 91-102, 2022 | 107 | 2022 |
The role of pre-training data in transfer learning R Entezari, M Wortsman, O Saukh, MM Shariatnia, H Sedghi, L Schmidt arXiv preprint arXiv:2302.13602, 2023 | 19 | 2023 |
Deep learning model for measurement of shoulder critical angle and acromion index on shoulder radiographs MM Shariatnia, T Ramazanian, J Sanchez-Sotelo, HM Kremers JSES Reviews, Reports, and Techniques 2 (3), 297-301, 2022 | 8 | 2022 |
Predictive modeling for acute kidney injury after percutaneous coronary intervention in patients with acute coronary syndrome: a machine learning approach AH Behnoush, MM Shariatnia, A Khalaji, M Asadi, A Yaghoobi, M Rezaee, ... European Journal of Medical Research 29 (1), 76, 2024 | 5 | 2024 |
The role of pre-training data in transfer learning. 2023 R Entezari, M Wortsman, O Saukh, MM Shariatnia, H Sedghi, L Schmidt URL https://arxiv. org/abs/2302.13602, 0 | 3 | |
moein-shariatnia/OpenAI-CLIP: openai-clip-first-release M Shariatnia Zenodo, 2022 | 2 | 2022 |
How well do contrastively trained models transfer? MM Shariatnia, R Entezari, M Wortsman, O Saukh, L Schmidt First Workshop on Pre-training: Perspectives, Pitfalls, and Paths Forward at …, 2022 | 2 | 2022 |
Artificial intelligence correctly identifies perfect lateral knee X-rays: a pilot study FC Oettl, M Shariatnia, K Kunze, A Allen, A Ranawat, A Pearle, A Pareek | | 2024 |
CONFLARE: CONFormal LArge language model REtrieval P Rouzrokh, S Faghani, CU Gamble, M Shariatnia, BJ Erickson arXiv preprint arXiv:2404.04287, 2024 | | 2024 |