[HTML][HTML] A survey of large language models for healthcare: from data, technology, and applications to accountability and ethics

K He, R Mao, Q Lin, Y Ruan, X Lan, M Feng… - Information …, 2025 - Elsevier
The utilization of large language models (LLMs) for Healthcare has generated both
excitement and concern due to their ability to effectively respond to free-text queries with …

MentaLLaMA: interpretable mental health analysis on social media with large language models

K Yang, T Zhang, Z Kuang, Q **e, J Huang… - Proceedings of the …, 2024 - dl.acm.org
As an integral part of people's daily lives, social media is becoming a rich source for
automatic mental health analysis. As traditional discriminative methods bear poor …

Vision–language foundation model for echocardiogram interpretation

M Christensen, M Vukadinovic, N Yuan, D Ouyang - Nature Medicine, 2024 - nature.com
The development of robust artificial intelligence models for echocardiography has been
limited by the availability of annotated clinical data. Here, to address this challenge and …

Rethinking large language models in mental health applications

S Ji, T Zhang, K Yang, S Ananiadou… - arxiv preprint arxiv …, 2023 - arxiv.org
Large Language Models (LLMs) have become valuable assets in mental health, showing
promise in both classification tasks and counseling applications. This paper offers a …

Using large language models to detect outcomes in qualitative studies of adolescent depression

AW **n, DM Nielson, KR Krause… - Journal of the …, 2024 - academic.oup.com
Objective We aim to use large language models (LLMs) to detect mentions of nuanced
psychotherapeutic outcomes and impacts than previously considered in transcripts of …

Sentiment-guided Transformer with Severity-aware Contrastive Learning for Depression Detection on Social Media

T Zhang, K Yang, S Ananiadou - The 22nd Workshop on …, 2023 - aclanthology.org
Early identification of depression is beneficial to public health surveillance and disease
treatment. There are many models that mainly treat the detection as a binary classification …

AdaCLF: An Adaptive Curriculum Learning Framework for Emotional Support Conversation

G Tu, T Niu, R Xu, B Liang… - IEEE Intelligent …, 2024 - ieeexplore.ieee.org
Emotional support conversation (ESC) aims to alleviate emotional distress using data-driven
approaches trained on human-generated responses. However, the subjective and open …

Pre-training Differentially Private Models with Limited Public Data

Z Bu, X Zhang, M Hong, S Zha, G Karypis - arxiv preprint arxiv …, 2024 - arxiv.org
The superior performance of large foundation models relies on the use of massive amounts
of high-quality data, which often contain sensitive, private and copyrighted material that …

AI and narrative embeddings detect PTSD following childbirth via birth stories

A Bartal, KM Jagodnik, SJ Chan, S Dekel - Scientific Reports, 2024 - nature.com
Free-text analysis using machine learning (ML)-based natural language processing (NLP)
shows promise for diagnosing psychiatric conditions. Chat Generative Pre-trained …

[PDF][PDF] ChatGPT demonstrates potential for identifying psychiatric disorders: application to childbirth-related post-traumatic stress disorder

A Bartal, KM Jagodnik, SJ Chan… - Research …, 2023 - pdfs.semanticscholar.org
Free-text analysis using Machine Learning (ML)-based Natural Language Processing (NLP)
shows promise for diagnosing psychiatric conditions. Chat Generative Pre-trained …