no code implementations • 23 Apr 2024 • Clément Christophe, Praveen K Kanithi, Prateek Munjal, Tathagata Raha, Nasir Hayat, Ronnie Rajan, Ahmed Al-Mahrooqi, Avani Gupta, Muhammad Umar Salman, Gurpreet Gosal, Bhargav Kanakiya, Charles Chen, Natalia Vassilieva, Boulbaba Ben Amor, Marco AF Pimentel, Shadab Khan
This study presents a comprehensive analysis and comparison of two predominant fine-tuning methodologies - full-parameter fine-tuning and parameter-efficient tuning - within the context of medical Large Language Models (LLMs).
1 code implementation • 14 Jul 2022 • Nasir Hayat, Krzysztof J. Geras, Farah E. Shamout
Multi-modal fusion approaches aim to integrate information from different data sources.
Ranked #1 on Phenotype classification on MIMIC-CXR, MIMIC-IV
no code implementations • 4 Nov 2021 • Nasir Hayat, Krzysztof J. Geras, Farah E. Shamout
The healthcare domain is characterized by heterogeneous data modalities, such as imaging and physiological data.
1 code implementation • 14 Jul 2021 • Nasir Hayat, Hazem Lashen, Farah E. Shamout
Here, we propose a multi-label generalized zero shot learning (CXR-ML-GZSL) network that can simultaneously predict multiple seen and unseen diseases in CXR images.
1 code implementation • 28 Nov 2020 • Ghadeer O. Ghosheh, Bana Alamad, Kai-Wen Yang, Faisil Syed, Nasir Hayat, Imran Iqbal, Fatima Al Kindi, Sara Al Junaibi, Maha Al Safi, Raghib Ali, Walid Zaher, Mariam Al Harbi, Farah E. Shamout
In test set B (225 patient encounters), the respective system achieves 0. 90 AUROC for AKI, elevated troponin, and elevated interleukin-6, and >0. 80 AUROC for most of the other complications.
2 code implementations • 19 Oct 2020 • Nasir Hayat, Munawar Hayat, Shafin Rahman, Salman Khan, Syed Waqas Zamir, Fahad Shahbaz Khan
The existing zero-shot detection approaches project visual features to the semantic domain for seen objects, hoping to map unseen objects to their corresponding semantics during inference.
Ranked #1 on Zero-Shot Object Detection on ImageNet Detection
2 code implementations • CVPR 2022 • Prateek Munjal, Nasir Hayat, Munawar Hayat, Jamshid Sourati, Shadab Khan
Finally, we conclude with a set of recommendations on how to assess the results using a new AL algorithm to ensure results are reproducible and robust under changes in experimental conditions.
Ranked #6 on Active Learning on CIFAR10 (10,000)