Search Results for author: Ishani Mondal

Found 16 papers, 5 papers with code

Extracting Semantic Aspects for Structured Representation of Clinical Trial Eligibility Criteria

no code implementations EMNLP (ClinicalNLP) 2020 Tirthankar Dasgupta, Ishani Mondal, Abir Naskar, Lipika Dey

Eligibility criteria in the clinical trials specify the characteristics that a patient must or must not possess in order to be treated according to a standard clinical care guideline.

Language Patterns and Behaviour of the Peer Supporters in Multilingual Healthcare Conversational Forums

no code implementations LREC 2022 Ishani Mondal, Kalika Bali, Mohit Jain, Monojit Choudhury, Jacki O’Neill, Millicent Ochieng, Kagnoya Awori, Keshet Ronen

In this work, we conduct a quantitative linguistic analysis of the language usage patterns of multilingual peer supporters in two health-focused WhatsApp groups in Kenya comprising of youth living with HIV.

Intent Identification and Entity Extraction for Healthcare Queries in Indic Languages

1 code implementation19 Feb 2023 Ankan Mullick, Ishani Mondal, Sourjyadip Ray, R Raghav, G Sai Chaitanya, Pawan Goyal

Scarcity of data and technological limitations for resource-poor languages in developing countries like India poses a threat to the development of sophisticated NLU systems for healthcare.

Explaining (Sarcastic) Utterances to Enhance Affect Understanding in Multimodal Dialogues

1 code implementation20 Nov 2022 Shivani Kumar, Ishani Mondal, Md Shad Akhtar, Tanmoy Chakraborty

To this end, we explore the task of Sarcasm Explanation in Dialogues, which aims to unfold the hidden irony behind sarcastic utterances.

Emotion Recognition Natural Language Understanding +1

Multi-Objective Few-shot Learning for Fair Classification

no code implementations5 Oct 2021 Ishani Mondal, Procheta Sen, Debasis Ganguly

In this paper, we propose a general framework for mitigating the disparities of the predicted classes with respect to secondary attributes within the data (e. g., race, gender etc.).

Classification Few-Shot Learning

End-to-End NLP Knowledge Graph Construction

no code implementations2 Jun 2021 Ishani Mondal, Yufang Hou, Charles Jochim

This paper studies the end-to-end construction of an NLP Knowledge Graph (KG) from scientific papers.

graph construction

BERTChem-DDI : Improved Drug-Drug Interaction Prediction from text using Chemical Structure Information

no code implementations AACL (knlp) 2020 Ishani Mondal

Traditional biomedical version of embeddings obtained from pre-trained language models have recently shown state-of-the-art results for relation extraction (RE) tasks in the medical domain.

Relation Extraction

Towards Incorporating Entity-specific Knowledge Graph Information in Predicting Drug-Drug Interactions

no code implementations21 Dec 2020 Ishani Mondal

In this paper, we explore how to incorporate domain knowledge of the biomedical entities (such as drug, disease, genes), obtained from Knowledge Graph (KG) Embeddings, for predicting Drug-Drug Interaction from textual corpus.

Natural Language Understanding Relation Classification

Medical Entity Linking using Triplet Network

no code implementations WS 2019 Ishani Mondal, Sukannya Purkayastha, Sudeshna Sarkar, Pawan Goyal, Jitesh Pillai, Amitava Bhattacharyya, Mahanandeeshwar Gattu

Entity linking (or Normalization) is an essential task in text mining that maps the entity mentions in the medical text to standard entities in a given Knowledge Base (KB).

Entity Linking

ALEX: Active Learning based Enhancement of a Model's Explainability

no code implementations2 Sep 2020 Ishani Mondal, Debasis Ganguly

An active learning (AL) algorithm seeks to construct an effective classifier with a minimal number of labeled examples in a bootstrapping manner.

Active Learning

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