1 citations · 1 across the 4 of their papers we have counts for
5 papers
Meta-learning Pathologies from Radiology Reports using Variance Aware Prototypical Networks
Arijit Sehanobish, Kawshik Kannan, Nabila Abraham +2
Large pretrained Transformer-based language models like BERT and GPT have changed the landscape of Natural Language Processing (NLP). However, fine tuning such models still require…
Explaining the Effectiveness of Multi-Task Learning for Efficient Knowledge Extraction from Spine MRI Reports
Arijit Sehanobish, McCullen Sandora, Nabila Abraham +7
Pretrained Transformer based models finetuned on domain specific corpora have changed the landscape of NLP. However, training or fine-tuning these models for individual tasks can b…
Transfer Learning with intelligent training data selection for prediction of Alzheimer's Disease
Naimul Mefraz Khan, Marcia Hon, Nabila Abraham
Detection of Alzheimer's Disease (AD) from neuroimaging data such as MRI through machine learning has been a subject of intense research in recent years. Recent success of deep lea…
Machine Learning on Biomedical Images: Interactive Learning, Transfer Learning, Class Imbalance, and Beyond
Naimul Mefraz Khan, Nabila Abraham, Ling Guan
In this paper, we highlight three issues that limit performance of machine learning on biomedical images, and tackle them through 3 case studies: 1) Interactive Machine Learning (I…
A Novel Focal Tversky loss function with improved Attention U-Net for lesion segmentation
Nabila Abraham, Naimul Mefraz Khan
We propose a generalized focal loss function based on the Tversky index to address the issue of data imbalance in medical image segmentation. Compared to the commonly used Dice los…