TNANet: A Temporal-Noise-Aware Neural Network for Suicidal Ideation Prediction with Noisy Physiological Data

N Liu, F Liu, W Ji, X Du, X Liu, G Zhao, W Mu… - arXiv preprint arXiv …, 2024 - arxiv.org
The robust generalization of deep learning models in the presence of inherent noise
remains a significant challenge, especially when labels are subjective and noise is …

Process knowledge-infused learning for suicidality assessment on social media

K Roy, M Gaur, Q Zhang, A Sheth - arXiv preprint arXiv:2204.12560, 2022 - arxiv.org
Improving the performance and natural language explanations of deep learning algorithms
is a priority for adoption by humans in the real world. In several domains, such as …

A transformer based approach to detect suicidal ideation using pre-trained language models

F Haque, RU Nur, S Al Jahan… - … on computer and …, 2020 - ieeexplore.ieee.org
Detection of Suicidal Ideation in social media has gained special attention in recent years.
Different mental health issues like depression, frustration, hopelessness etc directly or …

Deep sequential models for suicidal ideation from multiple source data

I Peis, PM Olmos, C Vera-Varela… - IEEE journal of …, 2019 - ieeexplore.ieee.org
This paper presents a novel method for predicting suicidal ideation from electronic health
records (EHR) and ecological momentary assessment (EMA) data using deep sequential …

Suicidal ideation prediction based on social media posts using a GAN-infused deep learning framework with genetic optimization and word embedding fusion

R Kancharapu, SN Ayyagari - International Journal of Information …, 2024 - Springer
This study tackles the pressing issue of predicting suicidal tendencies on Twitter by
introducing an inventive methodology that integrates Generative Adversarial Networks …

Learning models for suicide prediction from social media posts

N Wang, F Luo, Y Shivtare, VD Badal… - arXiv preprint arXiv …, 2021 - arxiv.org
We propose a deep learning architecture and test three other machine learning models to
automatically detect individuals that will attempt suicide within (1) 30 days and (2) six …

Advanced deep learning and large language models for suicide ideation detection on social media

M Qorich, R El Ouazzani - Progress in Artificial Intelligence, 2024 - Springer
Recently, suicide ideations represent a worldwide health concern and pose many
anticipation challenges. Actually, the prevalence of expressing self-destructive thoughts …

Suicide Ideation Detection: Harnessing Machine and Deep Learning for Early Risk Identification

H Gupta, KK Gola, S Kumar, P Kumar… - 2023 6th International …, 2023 - ieeexplore.ieee.org
The prevalence of suicide and depression has become a growing concern worldwide. Early
detection of individuals at risk plays a crucial role in providing timely interventions and …

SOS-1K: A Fine-grained Suicide Risk Classification Dataset for Chinese Social Media Analysis

H Qi, H Liu, J Li, Q Zhao, W Zhai, D Luo, TY He… - arXiv preprint arXiv …, 2024 - arxiv.org
In the social media, users frequently express personal emotions, a subset of which may
indicate potential suicidal tendencies. The implicit and varied forms of expression in internet …

Predicting Suicide Cases Using Deep Neural Network

MM Ghaemi, H Ehtemam, F Ghasemian… - Science and Information …, 2024 - Springer
Suicide is a critical issue in contemporary society, giving rise to significant societal and
economic ramifications. To mitigate these adverse effects, it is imperative to implement …