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

Survival Curves01:18

Survival Curves

Survival curves are graphical representations that depict the survival experience of a population over time, offering an intuitive way to track the proportion of individuals who remain event-free at each time point. These curves are widely used in fields such as medicine, public health, and reliability engineering to visualize and compare survival probabilities across different groups or conditions.
The Kaplan-Meier estimator is the most common method for constructing survival curves. This...
Fundamental Mathematical Principles in Pharmacokinetics: Calculus and Graphs01:21

Fundamental Mathematical Principles in Pharmacokinetics: Calculus and Graphs

The fundamental mathematical principles, such as calculus and graphs, play crucial roles in analyzing drug movement and determining pharmacokinetic parameters. Differential calculus examines rates of change and helps to determine the dissolution rate of drugs in biofluids, as well as how drug concentrations change over time. For instance, it can help calculate the rate of elimination of a drug from the body based on its concentration-time profile.
On the other hand, integral calculus focuses on...
Introduction To Survival Analysis01:18

Introduction To Survival Analysis

Survival analysis is a statistical method used to study time-to-event data, where the "event" might represent outcomes like death, disease relapse, system failure, or recovery. A unique feature of survival data is censoring, which occurs when the event of interest has not been observed for some individuals during the study period. This requires specialized techniques to handle incomplete data effectively.
The primary goal of survival analysis is to estimate survival time—the time until a...
Comparing the Survival Analysis of Two or More Groups01:20

Comparing the Survival Analysis of Two or More Groups

Survival analysis is a cornerstone of medical research, used to evaluate the time until an event of interest occurs, such as death, disease recurrence, or recovery. Unlike standard statistical methods, survival analysis is particularly adept at handling censored data—instances where the event has not occurred for some participants by the end of the study or remains unobserved. To address these unique challenges, specialized techniques like the Kaplan-Meier estimator, log-rank test, and Cox...
Guidelines for Sketching a Curve01:23

Guidelines for Sketching a Curve

Curve sketching is a systematic method for understanding the overall behavior of a function by analyzing its key mathematical features. A function defines a curve on the coordinate plane, where the horizontal axis represents the input variable and the vertical axis represents the output. The process begins by determining the domain, which specifies the set of input values for which the function is defined and establishes the horizontal extent of the graph.Intercepts with the horizontal and...
Area Problem01:26

Area Problem

Determining the area of a region with straight edges is straightforward, as geometric formulas for rectangles, triangles, and polygons can be applied directly. However, traditional geometric methods are insufficient when a region has a curved boundary, such as the area under a function.fromThe area problem involves finding a systematic way to measure such regions. One approach to solving this problem is through approximation. Instead of attempting to compute the area exactly at the outset, the...

You might also read

Related Articles

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

Sort by
Same author

Combining genome-wide polygenic scores with registry data for colorectal cancer risk-based screening.

British journal of cancer·2026
Same author

Diagnostic performance of real-time characterization in artificial intelligence-assisted colonoscopy.

Endoscopy international open·2026
Same author

Long-term survival in generalized peritonitis: the impact of early critical periods in major emergency abdominal surgery.

BMC surgery·2026
Same author

The effect of dexamethasone on inflammatory markers of surgical stress: a randomized trial in robotic hysterectomy.

BMC surgery·2026
Same author

Response to Koulaouzidis et al. and Sharma et al.

Journal of the National Cancer Institute·2026
Same author

Whole Blood Transcriptomic Response to Perioperative Dexamethasone in Total Knee Arthroplasty: A Targeted Panel Analysis.

Acta anaesthesiologica Scandinavica·2026

Related Experiment Video

Updated: Jul 5, 2026

Utilizing a 3D Printed Laparoscopic Nissen Fundoplication Model to Shorten a Resident's Learning Curve
08:21

Utilizing a 3D Printed Laparoscopic Nissen Fundoplication Model to Shorten a Resident's Learning Curve

Published on: August 15, 2025

[Problems concerning analysis of learning curves in surgery].

Lars Peter Holst Andersen1, Ismail Gögenur, Jacob Rosenberg

  • 1Kirurgisk Gastroenterologisk Afdeling D, Gentofte Hospital, DK-2900 Hellerup. larspeter@stud.ku.dk.

Ugeskrift for Laeger
|May 22, 2008
PubMed
Summary

Analyzing surgical learning curves is complex. This paper discusses challenges in interpreting operative time, conversion rates, and complications to assess surgeon skill effectively.

Related Experiment Videos

Last Updated: Jul 5, 2026

Utilizing a 3D Printed Laparoscopic Nissen Fundoplication Model to Shorten a Resident's Learning Curve
08:21

Utilizing a 3D Printed Laparoscopic Nissen Fundoplication Model to Shorten a Resident's Learning Curve

Published on: August 15, 2025

Area of Science:

  • Surgical Education
  • Medical Technology Assessment

Background:

  • Laparoscopic surgery necessitates evaluating surgeon technical skills.
  • Traditional learning curve metrics include operative time, conversion rates, and complications.

Purpose of the Study:

  • To address challenges in analyzing surgical learning curves.
  • To improve the interpretation of surgeon skill acquisition in minimally invasive procedures.

Main Methods:

  • Review of existing literature on surgical learning curves.
  • Discussion of statistical and methodological issues in data interpretation.

Main Results:

  • Learning curves in surgery are complex and not always straightforward to interpret.
  • Commonly used parameters may not fully capture the nuances of surgical learning.

Conclusions:

  • A critical approach is needed for analyzing surgical learning curves.
  • Further research should focus on more robust methods for skill assessment in surgery.