Related Experiment Video

Updated: Jun 9, 2025

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack
07:31

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

Published on: May 15, 2020

7.0K

Publisher Correction: Development and assessment of a machine learning tool for predicting emergency admission in

James Liley1,2,3, Gergo Bohner4,5, Samuel R Emerson6

  • 1Department of Mathematical Sciences, Durham University, Durham, UK. james.liley@durham.ac.uk.

NPJ Digital Medicine
|October 27, 2024
PubMed
Abstract

No abstract available in PubMed .

More Related Videos

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
12:18

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment

Published on: January 11, 2020

7.5K
Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma
04:09

Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma

Published on: October 10, 2018

8.2K

Related Experiment Videos

Last Updated: Jun 9, 2025

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack
07:31

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

Published on: May 15, 2020

7.0K
A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
12:18

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment

Published on: January 11, 2020

7.5K
Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma
04:09

Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma

Published on: October 10, 2018

8.2K

Related Concept Videos

Steps in Outbreak Investigation01:18

Steps in Outbreak Investigation

107
In the ever-evolving field of public health, statistical analysis serves as a cornerstone for understanding and managing disease outbreaks. By leveraging various statistical tools, health professionals can predict potential outbreaks, analyze ongoing situations, and devise effective responses to mitigate impact. For that to happen, there are a few possible stages of the analysis:
107

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

Massive aortic thrombus in a hypercoagulable patient with heparin induced thrombocytopenia: a case report.

Journal of surgical case reports·2026

Human evaluators vs. LLM-as-a-Judge: toward scalable evaluation of GenAI in global health.

NPJ digital medicine·2026

MiracleNet: A Biologically Interpretable Machine Learning Model for Resected Non-small-cell Lung Cancer.

Computational and structural biotechnology journal·2026

Generative AI-enabled clinical decision support system in primary care: a pragmatic, cluster-randomized trial.

Nature medicine·2026

Development and validation of a risk assessment model for hospital-acquired venous thrombosis in medical in-patients with cancer.

Journal of thrombosis and haemostasis : JTH·2026

Safety of a large language model-based clinical decision support system in African primary healthcare.

Nature health·2026

A scoping review on the mental health harms of LLM-based chatbots.

NPJ digital medicine·2026

Fully-automated sleep staging for Parkinson's disease and isolated REM sleep behavior disorder.

NPJ digital medicine·2026

Real-world use of large language models for mental health in 2024.

NPJ digital medicine·2026

Role prompting modulates linguistic style but not clinical decision structure in GPT-5 tumour board simulation.

NPJ digital medicine·2026

Reply to: Surgical scene understanding and the emerging challenge of independent validation in an industry-led AI ecosystem.

NPJ digital medicine·2026

Surgical scene understanding and the structural validation gap in an industry-led AI ecosystem.

NPJ digital medicine·2026

Visual Attention Prompted Prediction and Learning.

IJCAI : proceedings of the conference·2026

DUE: Dynamic Uncertainty-Aware Explanation Supervision via 3D Imputation.

KDD : proceedings. International Conference on Knowledge Discovery & Data Mining·2026

Fast and featureless node representation learning with partial pairwise supervision.

Neural networks : the official journal of the International Neural Network Society·2026

RAMCF: Rank-Aware Multimodal Contrastive Framework for drug side-effect frequency prediction.

Computational biology and chemistry·2026

Validation of federated analytics across secure data environments: A comparative study of synthetic healthcare datasets using machine learning and general linear models.

Digital health·2026

Multimodal integrated knowledge transfer to large language models through preference optimization with biomedical applications.

Patterns (New York, N.Y.)·2026
See all related articles
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies
Jove
Visualize
Contact Us