2 citations · 2 across the 2 of their papers we have counts for
6 papers
3N-GAN: Semi-Supervised Classification of X-Ray Images with a 3-Player Adversarial Framework
Shafin Haque, Ayaan Haque
The success of deep learning for medical imaging tasks, such as classification, is heavily reliant on the availability of large-scale datasets. However, acquiring datasets with lar…
Convolutional Nets for Diabetic Retinopathy Screening in Bangladeshi Patients
Ayaan Haque, Ipsita Sutradhar, Mahziba Rahman +2
Diabetes is one of the most prevalent chronic diseases in Bangladesh, and as a result, Diabetic Retinopathy (DR) is widespread in the population. DR, an eye illness caused by diabe…
Window-Level is a Strong Denoising Surrogate
Ayaan Haque, Adam Wang, Abdullah-Al-Zubaer Imran
CT image quality is heavily reliant on radiation dose, which causes a trade-off between radiation dose and image quality that affects the subsequent image-based diagnostic performa…
Deep Learning for Suicide and Depression Identification with Unsupervised Label Correction
Ayaan Haque, Viraaj Reddi, Tyler Giallanza
Early detection of suicidal ideation in depressed individuals can allow for adequate medical attention and support, which in many cases is life-saving. Recent NLP research focuses…
EC-GAN: Low-Sample Classification using Semi-Supervised Algorithms and GANs
Ayaan Haque
Semi-supervised learning has been gaining attention as it allows for performing image analysis tasks such as classification with limited labeled data. Some popular algorithms using…
MultiMix: Sparingly Supervised, Extreme Multitask Learning From Medical Images
Ayaan Haque, Abdullah-Al-Zubaer Imran, Adam Wang +1
Semi-supervised learning via learning from limited quantities of labeled data has been investigated as an alternative to supervised counterparts. Maximizing knowledge gains from co…