Jove
Visualize
Contact Us
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

Related Concept Videos

Phase-lead and Phase-lag Controllers01:22

Phase-lead and Phase-lag Controllers

539
Understanding the working function of different types of controllers can be illustrated with practical analogies, such as adjusting a stereo's volume equalizer. Cranking up the bass involves a phase-lead controller, which functions as a high-pass filter, while increasing the treble uses a phase-lag controller, which acts as a low-pass filter. PD controllers, similar to high-pass filters, enhance the system's response to high-frequency components. PI controllers, akin to low-pass...
539
Lagging Strand Synthesis01:59

Lagging Strand Synthesis

61.3K
During replication, the complementary strands in double-stranded DNA are synthesized at different rates. Replication first begins on the leading strand. Replication starts later, occurs more slowly, and proceeds discontinuously on the lagging strand.
There are several major differences between synthesis of the leading strand and synthesis of the lagging strand. 1) Leading strand synthesis happens in the direction of replication fork opening, whereas lagging strand synthesis happens in the...
61.3K
Lagging Strand Synthesis01:59

Lagging Strand Synthesis

16.6K
16.6K
Time and frequency -Domain Interpretation of Phase-lag Control01:21

Time and frequency -Domain Interpretation of Phase-lag Control

414
Phase-lag controllers are widely used in control systems to improve stability and reduce steady-state errors. A dimmer switch controlling the brightness of a light bulb serves as a practical example of phase-lag control, gradually adjusting the bulb's brightness. Mathematically, phase-lag control or low-pass filtering is represented when the factor 'a' is less than 1.
Phase-lag controllers do not place a pole at zero, but instead influence the steady-state error by amplifying any...
414
Convolution Properties II01:17

Convolution Properties II

582
The important convolution properties include width, area, differentiation, and integration properties.
The width property indicates that if the durations of input signals are T1 and T2, then the width of the output response equals the sum of both durations, irrespective of the shapes of the two functions. For instance, convolving two rectangular pulses with durations of 2 seconds and 1 second results in a function with a width of 3 seconds.
The area property asserts that the area under the...
582
Convolution Properties I01:20

Convolution Properties I

581
Convolution computations can be simplified by utilizing their inherent properties.
The commutative property reveals that the input and the impulse response of an LTI (Linear Time-Invariant) system can be interchanged without affecting the output:
581

You might also read

Related Articles

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

Sort by
Same author

Deriving Clavien-Dindo Classification from Administrative Data: Development and External Validation in Hepatobiliary Surgery.

Annals of surgery·2026
Same author

A regularized multi-state model for covariate selection with interval-censored survival data.

Biometrics·2026
Same author

COBT: a gene-based rare variant burden test for case-only study designs using aggregated genotypes from public reference cohorts.

Genome medicine·2026
Same author

Sharp Bounds for Continuous-Valued Treatment Effects with Unobserved Confounders.

Biometrical journal. Biometrische Zeitschrift·2025
Same author

Proposition of a new, minimally-invasive, software smartphone device to predict sleep apnea and its severity.

Sleep & breathing = Schlaf & Atmung·2025
Same author

Evaluating breast cancer screening performance without registries using medico-administrative data.

Scientific reports·2025

Related Experiment Video

Updated: Jan 28, 2026

Author Spotlight: Exploring Microglial Interactions with Stress-Response Circuitry Using the Limited Bedding and Nesting Model
04:20

Author Spotlight: Exploring Microglial Interactions with Stress-Response Circuitry Using the Limited Bedding and Nesting Model

Published on: July 12, 2024

2.5K

ConvSCCS: convolutional self-controlled case series model for lagged adverse event detection.

Maryan Morel1, Emmanuel Bacry2, Stéphane Gaïffas3

  • 1CMAP Ecole Polytechnique, 91128 Palaiseau Cedex, France.

Biostatistics (Oxford, England)
|March 10, 2019
PubMed
Summary

This study introduces a novel self-controlled case series (SCCS) model to improve the detection of adverse drug reactions (ADRs) using electronic health records. The new method enhances risk screening by analyzing multiple drug exposures and rare outcomes more effectively.

Keywords:
Conditional Poisson modelPenalizationRisk screeningScalabilitySelf-controlled case seriesTotal variation

More Related Videos

ScanLag: High-throughput Quantification of Colony Growth and Lag Time
07:47

ScanLag: High-throughput Quantification of Colony Growth and Lag Time

Published on: July 15, 2014

16.8K
Microfluidic Model to Mimic Initial Event of Neovascularization
10:01

Microfluidic Model to Mimic Initial Event of Neovascularization

Published on: April 10, 2021

5.2K

Related Experiment Videos

Last Updated: Jan 28, 2026

Author Spotlight: Exploring Microglial Interactions with Stress-Response Circuitry Using the Limited Bedding and Nesting Model
04:20

Author Spotlight: Exploring Microglial Interactions with Stress-Response Circuitry Using the Limited Bedding and Nesting Model

Published on: July 12, 2024

2.5K
ScanLag: High-throughput Quantification of Colony Growth and Lag Time
07:47

ScanLag: High-throughput Quantification of Colony Growth and Lag Time

Published on: July 15, 2014

16.8K
Microfluidic Model to Mimic Initial Event of Neovascularization
10:01

Microfluidic Model to Mimic Initial Event of Neovascularization

Published on: April 10, 2021

5.2K

Area of Science:

  • Health Informatics
  • Pharmacovigilance
  • Statistical Modeling

Background:

  • Electronic health records (EHRs) offer opportunities for improved health risk screening.
  • Current methods for detecting adverse drug reactions (ADRs) often rely on under-reported spontaneous physician reports.
  • Developing scalable models for analyzing longitudinal health data is crucial for enhancing post-marketing surveillance.

Purpose of the Study:

  • To develop a scalable statistical model for estimating the effect of multiple longitudinal drug exposures on rare longitudinal health outcomes.
  • To introduce a novel self-controlled case series (SCCS) model with flexible intensity modeling for enhanced ADR detection.
  • To improve upon existing methods in terms of accuracy and computational efficiency for relative risk estimation.

Main Methods:

  • Utilized a conditional Poisson regression model, specifically the self-controlled case series (SCCS) approach.
  • Modeled outcome intensity using a convolution of exposures and penalized step functions (group-Lasso and total-variation) to avoid precise risk period specification.
  • Developed a novel SCCS model capable of handling multiple longitudinal features within a single framework.

Main Results:

  • The proposed SCCS model demonstrated improved performance over the state-of-the-art in mean absolute error and computation time on simulated data.
  • The method was successfully applied to an ADR detection problem using a large cohort of diabetic patients from the French national health insurance database (SNIIRAM).
  • This represents the first SCCS model with flexible intensity that can accommodate multiple longitudinal features simultaneously.

Conclusions:

  • The developed SCCS model offers a significant advancement in analyzing longitudinal health data for ADR detection.
  • This approach enhances the utility of large electronic health records databases for public health surveillance.
  • The method provides a more accurate and efficient tool for identifying potential adverse drug reactions in real-world clinical settings.