activity
20182022
most citedClinical Prompt Learning with Frozen Language Models

6 citations · 6 across the 2 of their papers we have counts for

collaborators

8 papers

cs.CL20226 cited

Clinical Prompt Learning with Frozen Language Models

Niall Taylor, Yi Zhang, Dan Joyce +2

Prompt learning is a new paradigm in the Natural Language Processing (NLP) field which has shown impressive performance on a number of natural language tasks with common benchmarki…

cs.CL2020

An efficient representation of chronological events in medical texts

Andrey Kormilitzin, Nemanja Vaci, Qiang Liu +3

In this work we addressed the problem of capturing sequential information contained in longitudinal electronic health records (EHRs). Clinical notes, which is a particular type of…

cs.LG2020

Population Gradients improve performance across data-sets and architectures in object classification

Yurika Sakai, Andrey Kormilitzin, Qiang Liu +1

The most successful methods such as ReLU transfer functions, batch normalization, Xavier initialization, dropout, learning rate decay, or dynamic optimizers, have become standards…

cs.CL2020

Information Extraction from Swedish Medical Prescriptions with Sig-Transformer Encoder

John Pougue Biyong, Bo Wang, Terry Lyons +1

Relying on large pretrained language models such as Bidirectional Encoder Representations from Transformers (BERT) for encoding and adding a simple prediction layer has led to impr…

cs.CL2020

Med7: a transferable clinical natural language processing model for electronic health records

Andrey Kormilitzin, Nemanja Vaci, Qiang Liu +1

The field of clinical natural language processing has been advanced significantly since the introduction of deep learning models. The self-supervised representation learning and th…

eess.IV2019

Deep Learning for Estimating Synaptic Health of Primary Neuronal Cell Culture

Andrey Kormilitzin, Xinyu Yang, William H. Stone +5

Understanding the morphological changes of primary neuronal cells induced by chemical compounds is essential for drug discovery. Using the data from a single high-throughput imagin…