AIMC Topic: Text Messaging

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Testing a Machine Learning-Based Adaptive Motivational System for Socioeconomically Disadvantaged Smokers (Adapt2Quit): Protocol for a Randomized Controlled Trial.

JMIR research protocols Apr 16, 2025
BACKGROUND: Individuals who are socioeconomically disadvantaged have high smoking rates and face barriers to participating in smoking cessation interventions. Computer-tailored health communication, which is focused on finding the most relevant messa...
Male Middle Aged Vulnerable Populations Machine Learning Female Adult Smokers Smoking Cessation Text Messaging Randomized Controlled Trials as Topic Poverty Motivation Humans
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An Explainable Artificial Intelligence Text Classifier for Suicidality Prediction in Youth Crisis Text Line Users: Development and Validation Study.

JMIR public health and surveillance Jan 29, 2025
BACKGROUND: Suicide represents a critical public health concern, and machine learning (ML) models offer the potential for identifying at-risk individuals. Recent studies using benchmark datasets and real-world social media data have demonstrated the ...
Humans Artificial Intelligence Adolescent Suicidal Ideation Suicide Germany Text Messaging Adult Male Risk Assessment Female Young Adult
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The Most Effective Interventions for Classification Model Development to Predict Chat Outcomes Based on the Conversation Content in Online Suicide Prevention Chats: Machine Learning Approach.

JMIR mental health Sep 26, 2024
BACKGROUND: For the provision of optimal care in a suicide prevention helpline, it is important to know what contributes to positive or negative effects on help seekers. Helplines can often be contacted through text-based chat services, which produce...
Adult Male Middle Aged Machine Learning Female Hotlines Suicide Prevention Netherlands Text Messaging Humans
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Novel Machine Learning HIV Intervention for Sexual and Gender Minority Young People Who Have Sex With Men (uTECH): Protocol for a Randomized Comparison Trial.

JMIR research protocols Aug 20, 2024
BACKGROUND: Sexual and gender minority (SGM) young people are disproportionately affected by HIV in the United States, and substance use is a major driver of new infections. People who use web-based venues to meet sex partners are more likely to repo...
United States Sexual and Gender Minorities Randomized Controlled Trials as Topic Homosexuality, Male Text Messaging Male Adolescent HIV Infections Young Adult Adult Humans Machine Learning Female
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Assessing Artificial Intelligence-Generated Responses to Urology Patient In-Basket Messages.

Urology practice Jun 24, 2024
INTRODUCTION: Electronic patient messaging utilization has increased in recent years and has been associated with physician burnout. ChatGPT is a language model that has shown the ability to generate near-human level text responses. This study evalua...
Physician-Patient Relations Urology Text Messaging Humans Artificial Intelligence
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Large-Scale Textual Datasets and Deep Learning for the Prediction of Depressed Symptoms.

Computational intelligence and neuroscience Apr 12, 2022
Millions of people worldwide suffer from depression. Assessing, treating, and preventing recurrence requires early detection of depressive symptoms as depression-related datasets expand and machine learning improves, intelligent approaches to detect ...
Humans Neural Networks, Computer Machine Learning Text Messaging Deep Learning Adolescent
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A new ML-based approach to enhance student engagement in online environment.

PloS one Nov 10, 2021
The educational research is increasingly emphasizing the potential of student engagement and its impact on performance, retention and persistence. This construct has emerged as an important paradigm in the higher education field for many decades. How...
Videoconferencing Electronic Mail Feedback, Psychological Text Messaging Education, Distance Motivation Students Problem-Based Learning Humans Problem Solving Universities Neural Networks, Computer Support Vector Machine
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Generative Adversarial Networks for Creating Synthetic Free-Text Medical Data: A Proposal for Collaborative Research and Re-use of Machine Learning Models.

AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science May 17, 2021
Restrictions in sharing Patient Health Identifiers (PHI) limit cross-organizational re-use of free-text medical data. We leverage Generative Adversarial Networks (GAN) to produce synthetic unstructured free-text medical data with low re-identificatio...
Humans Machine Learning Text Messaging
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Identification of Gout Flares in Chief Complaint Text Using Natural Language Processing.

AMIA ... Annual Symposium proceedings. AMIA Symposium Jan 25, 2021
Many patients with gout flares treated in the Emergency Department (ED) often do not receive optimal continuity of care after an ED visit. Thus, developing methods to identify patients with gout flares in the ED and referring them to appropriate outp...
Emergency Service, Hospital Retrospective Studies Symptom Flare Up Humans Triage Text Messaging Algorithms Natural Language Processing Gout
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Deep-Learning-Based Prediction of High-Risk Taxi Drivers Using Wellness Data.

International journal of environmental research and public health Dec 18, 2020
BACKGROUND: Factors related to the wellness of taxi drivers are important for identifying high-risk drivers based on human factors. The purpose of this study is to predict high-risk taxi drivers based on a deep learning method by identifying the well...
Text Messaging Accidents, Traffic Humans Automobile Driving Deep Learning
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