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

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

104
Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
104
Extraction: Partition and Distribution Coefficients01:14

Extraction: Partition and Distribution Coefficients

3.2K
The distribution law or Nernst's distribution law is the law that governs the distribution of a solute between two immiscible solvents. This law, also known as the partition law, states that if a solute is added to the mixture of two immiscible solvents at a constant temperature, the solute is distributed between the two solvents in such a way that the ratio of solute concentrations in the solvents remains constant at equilibrium.
For extracting a solute from an aqueous phase into an...
3.2K
Residuals and Least-Squares Property01:11

Residuals and Least-Squares Property

7.9K
The vertical distance between the actual value of y and the estimated value of y. In other words, it measures the vertical distance between the actual data point and the predicted point on the line
If the observed data point lies above the line, the residual is positive, and the line underestimates the actual data value for y. If the observed data point lies below the line, the residual is negative, and the line overestimates the actual data value for y.
The process of fitting the best-fit...
7.9K
One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation01:24

One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation

738
This lesson introduces two critical methods in pharmacokinetics, the Wagner-Nelson and Loo-Riegelman methods, used for estimating the absorption rate constant (ka) for drugs administered via non-intravenous routes. The Wagner-Nelson method relates ka to the plasma concentration derived from the slope of a semilog percent unabsorbed time plot. However, it is limited to drugs with one-compartment kinetics and can be impacted by factors like gastrointestinal motility or enzymatic degradation.
On...
738
Quantifying and Rejecting Outliers: The Grubbs Test01:02

Quantifying and Rejecting Outliers: The Grubbs Test

2.2K
Sometimes, a data set can have a recorded numerical observation that greatly  deviates from the rest of the data. Assuming that the data is normally distributed, a statistical method called the Grubbs test can be used to determine whether the observation is truly an outlier.  To perform a two-tailed Grubbs test, first, calculate the absolute difference between the outlier and the mean. Then, calculate the ratio between this difference and the standard deviation of the sample. This...
2.2K
Maxwell-Boltzmann Distribution: Problem Solving01:20

Maxwell-Boltzmann Distribution: Problem Solving

1.8K
Individual molecules in a gas move in random directions, but a gas containing numerous molecules has a predictable distribution of molecular speeds, which is known as the Maxwell-Boltzmann distribution, f(v).
This distribution function f(v) is defined by saying that the expected number N (v1,v2) of particles with speeds between v1 and v2 is given by
1.8K

You might also read

Related Articles

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

Sort by
Same author

Prediction on a Missing Ferroelectric Butterfly Phosphorus Allotrope and Its Energy-Favorable Low-Dimensional Forms.

The journal of physical chemistry letters·2025
Same author

Phylogenetic Relationship and Characterization of the Complete Mitochondrial Genome of the Cuckoo Species <i>Clamator coromandus</i> (Aves: Cuculidae).

International journal of molecular sciences·2025
Same author

A Computational Framework Analysis of Public Attitudes Toward Male Human Papillomavirus Infection and Its Vaccination in China: Based on Weibo Data.

Healthcare (Basel, Switzerland)·2025
Same author

Harnessing near-infrared and Raman spectral sensing and artificial intelligence for real-time monitoring and precision control of bioprocess.

Bioresource technology·2025
Same author

Risk Factors, Microbiology, and Prognosis of Diabetic Foot Osteomyelitis: A Retrospective Cohort Study.

Endocrine practice : official journal of the American College of Endocrinology and the American Association of Clinical Endocrinologists·2025
Same author

Proton minibeam (pMBRT) radiation therapy: experimental validation of Monte Carlo dose calculation in the RayStation TPS.

Physics in medicine and biology·2025
Same journal

Decomposition-based harmonization for quantitative PET imaging across scanners and radiotracers.

Medical physics·2026
Same journal

Development and evaluation of an in vivo dose-based monitoring system for electron FLASH radiation therapy.

Medical physics·2026
Same journal

A novel optical respiratory gating system with a hybrid phase-amplitude algorithm for spot-scanning proton therapy.

Medical physics·2026
Same journal

Gamma Knife treatment planning using knowledge-based reinforcement learning.

Medical physics·2026
Same journal

Development and characterization of a novel, small animal external beam irradiator using a clinical high dose rate brachytherapy source.

Medical physics·2026
Same journal

Deep learning-based dose prediction for MR-guided prostate SIB: Supporting rapid feasibility assessment and adaptive editing margin selection.

Medical physics·2026
See all related articles

Related Experiment Video

Updated: Sep 19, 2025

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
11:53

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm

Published on: December 9, 2012

13.1K

Efficient operator-splitting minimax algorithm for robust optimization.

Jiulong Liu1, Ya-Nan Zhu2, Xiaoqun Zhang3

  • 1LSEC, Institute of Computational Mathematics and Scientific/Engineering Computing, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, China.

Medical Physics
|June 8, 2025
PubMed
Summary
This summary is machine-generated.

This study introduces an efficient operator-splitting (OS) minimax robust optimization algorithm for proton radiation therapy. The new method significantly improves treatment plan quality and reduces computation time compared to existing approaches.

Keywords:
IMPTproton therapyrobust optimization

More Related Videos

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances
07:35

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Published on: October 11, 2018

7.6K
A Workflow for Lipid Nanoparticle LNP Formulation Optimization using Designed Mixture-Process Experiments and Self-Validated Ensemble Models SVEM
13:54

A Workflow for Lipid Nanoparticle LNP Formulation Optimization using Designed Mixture-Process Experiments and Self-Validated Ensemble Models SVEM

Published on: August 18, 2023

5.0K

Related Experiment Videos

Last Updated: Sep 19, 2025

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
11:53

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm

Published on: December 9, 2012

13.1K
Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances
07:35

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Published on: October 11, 2018

7.6K
A Workflow for Lipid Nanoparticle LNP Formulation Optimization using Designed Mixture-Process Experiments and Self-Validated Ensemble Models SVEM
13:54

A Workflow for Lipid Nanoparticle LNP Formulation Optimization using Designed Mixture-Process Experiments and Self-Validated Ensemble Models SVEM

Published on: August 18, 2023

5.0K

Area of Science:

  • Medical Physics
  • Radiation Oncology
  • Computational Optimization

Background:

  • Proton radiation therapy (RT) accuracy is challenged by treatment uncertainties like patient positioning.
  • Robust optimization (RO) addresses these uncertainties in treatment planning.
  • The minimax approach within RO optimizes for the worst-case scenario in plan quality.

Purpose of the Study:

  • Develop an efficient minimax robust optimization algorithm for proton RT.
  • Enhance both treatment plan quality and computational efficiency.

Main Methods:

  • Reformulated the minimax problem for efficient solution using a first-order operator-splitting (OS) algorithm.
  • Split the problem into subproblems with closed-form solutions or efficient linear system solutions.

Main Results:

  • The OS method demonstrated superior plan quality, robustness, and computational efficiency over stochastic programming (SP) and minimax stochastic programming (MSP).
  • In a prostate case, OS reduced maximum target dose (118% vs. 140%/121%) and mean femoral head dose (24.8% vs. 28.6%/26.3%).
  • OS decreased computational time from 16.4 min (MSP) to 1.7 min and reduced target robustness variance (RV120) from 56.07/0.30 to 0.04.

Conclusions:

  • A novel operator-splitting minimax robust optimization method was developed.
  • This new method offers improved plan quality and computational efficiency compared to MSP and SP.
  • The OS approach represents a significant advancement in robust optimization for proton RT.