Search Results for author: Sunghwan Sohn

Found 8 papers, 0 papers with code

Reliability Analysis of Psychological Concept Extraction and Classification in User-penned Text

no code implementations12 Jan 2024 Muskan Garg, MSVPJ Sathvik, Amrit Chadha, Shaina Raza, Sunghwan Sohn

The social NLP research community witness a recent surge in the computational advancements of mental health analysis to build responsible AI models for a complex interplay between language use and self-perception.

Binary Classification

InterPrompt: Interpretable Prompting for Interrelated Interpersonal Risk Factors in Reddit Posts

no code implementations21 Nov 2023 MSVPJ Sathvik, Surjodeep Sarkar, Chandni Saxena, Sunghwan Sohn, Muskan Garg

Mental health professionals and clinicians have observed the upsurge of mental disorders due to Interpersonal Risk Factors (IRFs).

Explanation Generation

LOST: A Mental Health Dataset of Low Self-esteem in Reddit Posts

no code implementations8 Jun 2023 Muskan Garg, Manas Gaur, Raxit Goswami, Sunghwan Sohn

Low self-esteem and interpersonal needs (i. e., thwarted belongingness (TB) and perceived burdensomeness (PB)) have a major impact on depression and suicide attempts.

Clinical Knowledge Data Augmentation

Augmenting Reddit Posts to Determine Wellness Dimensions impacting Mental Health

no code implementations6 Jun 2023 Chandreen Liyanage, Muskan Garg, Vijay Mago, Sunghwan Sohn

Amid ongoing health crisis, there is a growing necessity to discern possible signs of Wellness Dimensions (WD) manifested in self-narrated text.

Data Augmentation Semantic Similarity +1

Clinical Concept Extraction: a Methodology Review

no code implementations24 Oct 2019 Sunyang Fu, David Chen, Huan He, Sijia Liu, Sungrim Moon, Kevin J Peterson, Feichen Shen, Li-Wei Wang, Yanshan Wang, Andrew Wen, Yiqing Zhao, Sunghwan Sohn, Hongfang Liu

Background Concept extraction, a subdomain of natural language processing (NLP) with a focus on extracting concepts of interest, has been adopted to computationally extract clinical information from text for a wide range of applications ranging from clinical decision support to care quality improvement.

Clinical Concept Extraction Decision Making

Applications of Natural Language Processing in Clinical Research and Practice

no code implementations NAACL 2019 Yanshan Wang, Ahmad Tafti, Sunghwan Sohn, Rui Zhang

Through this tutorial, we would like to introduce NLP methodologies and tools developed in the clinical domain, and showcase the real-world NLP applications in clinical research and practice at Mayo Clinic (the No.

Retrieval

Staggered NLP-assisted refinement for Clinical Annotations of Chronic Disease Events

no code implementations LREC 2016 Stephen Wu, Chung-Il Wi, Sunghwan Sohn, Hongfang Liu, Young Juhn

Domain-specific annotations for NLP are often centered on real-world applications of text, and incorrect annotations may be particularly unacceptable.

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