Search Results for author: Denis Newman-Griffis

Found 16 papers, 11 papers with code

Definition drives design: Disability models and mechanisms of bias in AI technologies

no code implementations16 Jun 2022 Denis Newman-Griffis, Jessica Sage Rauchberg, Rahaf Alharbi, Louise Hickman, Harry Hochheiser

The increasing deployment of artificial intelligence (AI) tools to inform decision making across diverse areas including healthcare, employment, social benefits, and government policy, presents a serious risk for disabled people, who have been shown to face bias in AI implementations.

Decision Making

Robust Knowledge Graph Completion with Stacked Convolutions and a Student Re-Ranking Network

1 code implementation ACL 2021 Justin Lovelace, Denis Newman-Griffis, Shikhar Vashishth, Jill Fain Lehman, Carolyn Penstein Rosé

We develop a deep convolutional network that utilizes textual entity representations and demonstrate that our model outperforms recent KG completion methods in this challenging setting.

Knowledge Graph Completion Re-Ranking

Introducing Information Retrieval for Biomedical Informatics Students

1 code implementation NAACL (TeachingNLP) 2021 Sanya B. Taneja, Richard D. Boyce, William T. Reynolds, Denis Newman-Griffis

Introducing biomedical informatics (BMI) students to natural language processing (NLP) requires balancing technical depth with practical know-how to address application-focused needs.

Information Retrieval Retrieval

Translational NLP: A New Paradigm and General Principles for Natural Language Processing Research

no code implementations NAACL 2021 Denis Newman-Griffis, Jill Fain Lehman, Carolyn Rosé, Harry Hochheiser

Natural language processing (NLP) research combines the study of universal principles, through basic science, with applied science targeting specific use cases and settings.

TextEssence: A Tool for Interactive Analysis of Semantic Shifts Between Corpora

1 code implementation NAACL 2021 Denis Newman-Griffis, Venkatesh Sivaraman, Adam Perer, Eric Fosler-Lussier, Harry Hochheiser

Embeddings of words and concepts capture syntactic and semantic regularities of language; however, they have seen limited use as tools to study characteristics of different corpora and how they relate to one another.

Automated Coding of Under-Studied Medical Concept Domains: Linking Physical Activity Reports to the International Classification of Functioning, Disability, and Health

1 code implementation27 Nov 2020 Denis Newman-Griffis, Eric Fosler-Lussier

Both classification and candidate selection approaches present distinct strengths for automated coding in under-studied domains, and we highlight that the combination of (i) a small annotated data set; (ii) expert definitions of codes of interest; and (iii) a representative text corpus is sufficient to produce high-performing automated coding systems.

Language Modelling

Improving Broad-Coverage Medical Entity Linking with Semantic Type Prediction and Large-Scale Datasets

1 code implementation1 May 2020 Shikhar Vashishth, Denis Newman-Griffis, Rishabh Joshi, Ritam Dutt, Carolyn Rose

To address the dearth of annotated training data for medical entity linking, we present WikiMed and PubMedDS, two large-scale medical entity linking datasets, and demonstrate that pre-training MedType on these datasets further improves entity linking performance.

Entity Disambiguation Entity Linking +2

Writing habits and telltale neighbors: analyzing clinical concept usage patterns with sublanguage embeddings

no code implementations WS 2019 Denis Newman-Griffis, Eric Fosler-Lussier

Natural language processing techniques are being applied to increasingly diverse types of electronic health records, and can benefit from in-depth understanding of the distinguishing characteristics of medical document types.

HARE: a Flexible Highlighting Annotator for Ranking and Exploration

1 code implementation IJCNLP 2019 Denis Newman-Griffis, Eric Fosler-Lussier

Exploration and analysis of potential data sources is a significant challenge in the application of NLP techniques to novel information domains.

Document Ranking

Classifying the reported ability in clinical mobility descriptions

no code implementations WS 2019 Denis Newman-Griffis, Ayah Zirikly, Guy Divita, Bart Desmet

Finally, we highlight several challenges in classifying performance assertions, including capturing information about sources of assistance, incorporating syntactic structure and negation scope, and handling new modalities at test time.

Natural Language Inference

Jointly Embedding Entities and Text with Distant Supervision

2 code implementations WS 2018 Denis Newman-Griffis, Albert M. Lai, Eric Fosler-Lussier

Learning representations for knowledge base entities and concepts is becoming increasingly important for NLP applications.

Embedding Transfer for Low-Resource Medical Named Entity Recognition: A Case Study on Patient Mobility

1 code implementation WS 2018 Denis Newman-Griffis, Ayah Zirikly

Functioning is gaining recognition as an important indicator of global health, but remains under-studied in medical natural language processing research.

Domain Adaptation Medical Named Entity Recognition +3

Insights into Analogy Completion from the Biomedical Domain

1 code implementation WS 2017 Denis Newman-Griffis, Albert M. Lai, Eric Fosler-Lussier

Analogy completion has been a popular task in recent years for evaluating the semantic properties of word embeddings, but the standard methodology makes a number of assumptions about analogies that do not always hold, either in recent benchmark datasets or when expanding into other domains.

Word Embeddings

Second-Order Word Embeddings from Nearest Neighbor Topological Features

1 code implementation23 May 2017 Denis Newman-Griffis, Eric Fosler-Lussier

We introduce second-order vector representations of words, induced from nearest neighborhood topological features in pre-trained contextual word embeddings.

named-entity-recognition Named Entity Recognition +3

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