Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Non-equilibrium in the Cell

Non-equilibrium in the Cell

An important concept in studying metabolism and energy is that of chemical equilibrium. Most chemical reactions are reversible. They can proceed in both directions, releasing energy into their environment in one direction, and absorbing it from the environment in the other direction. The same is true for the chemical reactions involved in cell metabolism, such as the breaking down and building up of proteins into and from individual amino acids, respectively. Reactants within a closed system...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Bound Water as a Reinforcing Element for Ultra-Strong Polyacrylamide.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)·2026

Same author

CAF-derived PAI-1 serves as an EGFR ligand and fuels KRAS-mutant pancreatic cancer.

Nature communications·2026

Same author

Effects of beta-cypermethrin on the antioxidant system and gut microbiota in Eisenia fetida.

Environmental toxicology and pharmacology·2026

Same author

Exploring Dynamic Changes in Empathic Capability Among Postgraduate Nursing Students During Clinical Internships: An Artificial Intelligence-Assisted Qualitative Study With Human-in-the-Loop Validation.

Nurse educator·2026

Same author

Savolitinib in MET-amplified gastric or gastroesophageal junction adenocarcinoma: a phase 2 trial.

Nature medicine·2026

Same author

Exploring the Relationship Between Job Satisfaction and Turnover Intentions Among CRNAs.

AANA journal·2026

Search research articles

Related Experiment Video

Updated: Aug 10, 2025

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack

Published on: May 15, 2020

Predicting suicidal and self-injurious events in a correctional setting using AI algorithms on unstructured medical

Hongxia Lu¹, Alex Barrett², Albert Pierce¹

¹Schmid College of Science and Technology, Chapman University, 1 University Drive, Orange, CA, USA.

Journal of Psychiatric Research

|February 11, 2023

Summary

Artificial intelligence (AI) can predict suicidal and self-injurious events in jails using progress notes. This AI approach improves healthcare triage and prevention efforts, outperforming traditional methods.

Keywords:

Class imbalance Deep learning Machine learning NLP Suicidal and self-injurious events Under sampling

More Related Videos

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention

Published on: December 15, 2023

A Computer-Based Platform for Aiding Clinicians in Eating Disorder Analysis and Diagnosis

A Computer-Based Platform for Aiding Clinicians in Eating Disorder Analysis and Diagnosis

Published on: May 10, 2022

Related Experiment Videos

Last Updated: Aug 10, 2025

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack

Published on: May 15, 2020

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention

Published on: December 15, 2023

A Computer-Based Platform for Aiding Clinicians in Eating Disorder Analysis and Diagnosis

A Computer-Based Platform for Aiding Clinicians in Eating Disorder Analysis and Diagnosis

Published on: May 10, 2022

Area of Science:

Medical Informatics
Artificial Intelligence
Public Health

Background:

Suicidal and self-injurious incidents in correctional settings strain resources and staff.
Traditional statistical analyses are limited by structured data collection and high implementation costs.

Purpose of the Study:

To extract actionable insights from medical and mental health progress notes using AI.
To predict suicidal and self-injurious events for improved healthcare triage and prevention in Orange County Jails.

Main Methods:

Utilized AI algorithms, specifically a Transformer Encoder model, to analyze unstructured progress note data.
Compared AI model performance using notes data alone versus a hybrid approach combining notes data with structured Electronic Health Record (EHR) data.
Employed under-sampling techniques to address class imbalance in the dataset.

Main Results:

Progress notes contained richer information on suicidal/injurious behaviors than structured EHR data.
The Transformer Encoder model using notes data achieved an AUC-ROC of 0.862, Sensitivity of 0.816, and Specificity of 0.738.
Integrating notes data into traditional Machine Learning models improved Sensitivity to 0.89 (AUC-ROC: 0.77, Specificity: 0.65).

Conclusions:

AI analysis of clinical notes offers a more effective method for predicting inmate self-harm than structured data alone.
Hybrid models incorporating AI-extracted features show promise for enhancing predictive accuracy.
Under-sampling is a viable strategy for managing imbalanced data in this context.