1 code implementation • 27 Sep 2022 • Vignav Ramesh, Nathan Andrew Chi, Pranav Rajpurkar
Current deep learning models trained to generate radiology reports from chest radiographs are capable of producing clinically accurate, clear, and actionable text that can advance patient care.
no code implementations • 24 Aug 2022 • Minhaj Nur Alam, Rikiya Yamashita, Vignav Ramesh, Tejas Prabhune, Jennifer I. Lim, R. V. P. Chan, Joelle Hallak, Theodore Leng, Daniel Rubin
CL based pretraining with NST significantly improves DL classification performance, helps the model generalize well (transferable from EyePACS to UIC data), and allows training with small, annotated datasets, therefore reducing ground truth annotation burden of the clinicians.
no code implementations • 23 May 2022 • Anton Kolonin, Vignav Ramesh
In the presented study, we discover that the so-called "transition freedom" metric appears superior for unsupervised tokenization purposes in comparison to statistical metrics such as mutual information and conditional probability, providing F-measure scores in range from 0. 71 to 1. 0 across explored multilingual corpora.
1 code implementation • 8 Jul 2021 • Vignav Ramesh
Several deaths due to malaria are byproducts of disparities in the social determinants of health; the current gold standard for diagnosing malaria requires microscopes, reagents, and other equipment that most patients of low socioeconomic brackets do not have access to.
1 code implementation • 17 May 2021 • Vignav Ramesh, Blaine Rister, Daniel L. Rubin
Chest X-rays of coronavirus disease 2019 (COVID-19) patients are frequently obtained to determine the extent of lung disease and are a valuable source of data for creating artificial intelligence models.
1 code implementation • 19 Apr 2021 • Vignav Ramesh, Anton Kolonin
Many current artificial general intelligence (AGI) and natural language processing (NLP) architectures do not possess general conversational intelligence--that is, they either do not deal with language or are unable to convey knowledge in a form similar to the human language without manual, labor-intensive methods such as template-based customization.
1 code implementation • 15 Mar 2021 • Vignav Ramesh, Mason Wang
The onset of coronavirus disease 2019 (COVID-19), an infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has sparked unprecedented change.
1 code implementation • 14 Nov 2020 • Vignav Ramesh, Anton Kolonin
Natural language segmentation (NLS), or text segmentation, refers to the process of dividing written text into meaningful units.