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

Diagnosing Acidosis and Alkalosis

Diagnosing Acidosis and Alkalosis

Diagnosing acid-base imbalances involves systematically analyzing arterial blood samples, focusing on three key measurements: pH, bicarbonate (HCO3−) concentration, and carbon dioxide partial pressure (PCO2). This analysis follows a four-step process that helps identify the imbalance's underlying cause and nature.
First, the pH level is assessed to determine whether the blood pH is normal (7.35–7.45), low (acidosis), or high (alkalosis).
Next, the PCO2 and...

Predicting Molecular Geometry

Predicting Molecular Geometry

VSEPR Theory for Determination of Electron Pair Geometries

What is Genetic Engineering?

What is Genetic Engineering?

Prediction Intervals

Prediction Intervals

The interval estimate of any variable is known as the prediction interval. It helps decide if a point estimate is dependable.
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y.

End Point Prediction: Gran Plot

End Point Prediction: Gran Plot

A Gran plot is used to predict the equivalence volume or endpoint of a potentiometric or acid-base titration without reaching the endpoint. Typically, titration data is collected as a function of the titrant's volume up to a point less than the equivalence volume and then transformed into a linear format. The straight line is extended to the x-axis, indicating the necessary titrant volume to achieve the equivalence point.
For potentiometric titration, the Gran plot is created by plotting...

Sensitivity, Specificity, and Predicted Value

Sensitivity, Specificity, and Predicted Value

In healthcare diagnostics, laboratory tests play a crucial role in identifying and diagnosing a wide range of medical conditions. However, interpreting test results is not always straightforward. An abnormal test result does not always confirm the presence of a disease, just as a normal result does not guarantee its absence. To assess the reliability of these diagnostic tools, healthcare practitioners rely on two key statistical indicators: sensitivity and specificity.
Sensitivity is the...

You might also read

Related Articles

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

Sort by

Same author

CNet-Cox for interpretable network biomarker discovery and survival risk scoring in precise breast cancer prognosis.

NPJ digital medicine·2026

Same author

Disparities in HIV Testing Among Spanish and English-Speaking Hispanic/Latino Men who have Sex with Men and Social Media Use.

AIDS and behavior·2026

Same author

PancDS in Real-World Practice: A Prospective Multicenter Validation of a Clinical Decision-Support System Bridging Experience Gaps in Pancreatic Lesion Diagnosis.

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

Same author

Predictability of complex networks.

Proceedings of the National Academy of Sciences of the United States of America·2026

Same author

Biochemical-knowledge-driven machine learning pipeline for generating potent antimicrobial peptides.

Briefings in bioinformatics·2026

Same author

AI-based multiomics profiling reveals complementary omics contributions to personalized prediction of cardiovascular disease.

Nature communications·2026

Same journal

Analysis of strength degradation of coal and rock masses and stability of mined areas under long term immersion environment.

PloS one·2026

Same journal

Biogenic Silver-Selenium nanocomposite with anticancer activity and potent efficacy against vancomycin-resistant Staphylococcus aureus.

PloS one·2026

Same journal

Preparation and physicochemical characterization of a biodegradable chitosan/carboxymethyl cellulose hydrogel synthesized in NaOH/urea medium.

PloS one·2026

Same journal

Action-guilt, survivor-guilt, and depression in combat-related PTSD.

PloS one·2026

Same journal

Explainable machine learning for predicting activities of daily living at discharge in stroke patients: A retrospective study using SHAP interpretability.

PloS one·2026

Same journal

Deep learning based two-way feature depiction model for brain tumor detection.

PloS one·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Feb 7, 2026

Pattern-based Search of Epigenomic Data Using GeNemo

Pattern-based Search of Epigenomic Data Using GeNemo

Published on: October 8, 2017

Using search engine big data for predicting new HIV diagnoses.

Sean D Young¹, Qingpeng Zhang²

¹University of California Institute for Prediction Technology, Department of Family Medicine, University of California Los Angeles, Los Angeles, California, United States of America.

|July 13, 2018

Summary

This summary is machine-generated.

Google search data can predict new HIV diagnoses cases. This study demonstrates the feasibility of using Google Trends to monitor and forecast public health issues like HIV at the state level.

More Related Videos

Prediction of HIV-1 Coreceptor Usage Tropism by Sequence Analysis using a Genotypic Approach

Prediction of HIV-1 Coreceptor Usage Tropism by Sequence Analysis using a Genotypic Approach

Published on: December 1, 2011

Genotypic Inference of HIV-1 Tropism Using Population-based Sequencing of V3

Genotypic Inference of HIV-1 Tropism Using Population-based Sequencing of V3

Published on: December 27, 2010

Related Experiment Videos

Last Updated: Feb 7, 2026

Pattern-based Search of Epigenomic Data Using GeNemo

Pattern-based Search of Epigenomic Data Using GeNemo

Published on: October 8, 2017

Prediction of HIV-1 Coreceptor Usage Tropism by Sequence Analysis using a Genotypic Approach

Prediction of HIV-1 Coreceptor Usage Tropism by Sequence Analysis using a Genotypic Approach

Published on: December 1, 2011

Genotypic Inference of HIV-1 Tropism Using Population-based Sequencing of V3

Genotypic Inference of HIV-1 Tropism Using Population-based Sequencing of V3

Published on: December 27, 2010

Area of Science:

Public Health Informatics
Epidemiological Modeling
Digital Epidemiology

Background:

Vast amounts of
Purpose of the Study
Main Methods
Main Results
Conclusions

Purpose of the Study:

Assess the feasibility of using Google search data to analyze and predict new HIV diagnoses cases in the United States.
Evaluate the potential of internet search engine data for public health surveillance.

Main Methods:

Collected HIV-related Google search volume data from 2007 to 2014.
Utilized state-level new HIV diagnoses data from CDC and AIDSVu.org.
Developed a negative binomial model incorporating LASSO regression for keyword selection.
Trained the model on historical data to predict new HIV diagnoses from 2011 to 2014.

Main Results:

Achieved an average R2 value of 0.99 between predicted and actual HIV cases.
Attained an average root-mean-square error (RMSE) of 108.75.
Demonstrated Google Trends as a feasible tool for predicting state-level HIV cases.

Conclusions:

Google Trends can be effectively utilized for predicting new HIV diagnoses at the state level.
Discussed implications for integrating these predictive models into public health monitoring and HIV surveillance systems.
Highlighted the potential of big data analytics for proactive public health interventions.