- Research on outpatient capacity planning combining lean thinking ...🔍
- Optimization of sliding windows IMRT treatment planning🔍
- A New Linear Programming Approach to Radiation Therapy ...🔍
- A New Radiotherapy Optimization Model Based on Equivalent ...🔍
- Designing Radiotherapy Plans with Elastic Constraints and Interior ...🔍
- Utilizing Problem Structure in Optimization of Radiation Therapy🔍
- Linear Optimization🔍
- 8.3.1 An Application of Linear Optimization🔍
Impact of Using Linear Optimization Models in Dose Planning for ...
Research on outpatient capacity planning combining lean thinking ...
proposed an integer linear programming model to determine the optimal layout of outpatient services to reduce the congestion in the waiting room ...
Optimization of sliding windows IMRT treatment planning
This paper proposes a linear optimization model for IMRT with sliding windows. This model directly incorporates a number of deliverability constraints.
A New Linear Programming Approach to Radiation Therapy ...
... linear model. We demonstrate the effectiveness of our approach on ... A New Linear Programming Approach to Radiation Therapy Treatment Planning Problems.
A New Radiotherapy Optimization Model Based on Equivalent ...
Intensity Modulated Radiation Therapy (IMRT) is currently one of the effective methods for the treatment of malignant tumors. To ensure that the ...
Designing Radiotherapy Plans with Elastic Constraints and Interior ...
Linear programming models have been used extensively to find "good" radio- therapy treatment plans. In fact, the first model proposed in ¼968 ...
Utilizing Problem Structure in Optimization of Radiation Therapy
For a review of motion effects and compensation approaches in radiotherapy, see [78]. 1.6 Treatment planning and IMRT. The goal of radiotherapy ...
A mathematical optimization model consists of an objective function and a set of constraints in the form of a system of equations or inequalities.
8.3.1 An Application of Linear Optimization - Video 1 - YouTube
... linear optimization is used to design radiation therapy treatments for cancer patients. License: Creative Commons BY-NC-SA More information ...
Machine learning insights into scapular stabilization for alleviating ...
... models and optimization techniques are most effective in predicting treatment outcomes among college students? ... with this model compared ...
Travelling salesman problem - Wikipedia
... optimization. It is used as a benchmark for many optimization methods. Even though the problem is computationally difficult, many heuristics and exact ...
Diuretic Strategies in Patients with Acute Decompensated Heart ...
The treatment groups defined by each treatment factor (mode and dose) were compared with the use of a linear model (for continuous end points), ...
TechRxiv (pronounced "tech archive") is an open, moderated preprint server for unpublished research in the areas of engineering, computer science, and related ...
Monte Carlo method - Wikipedia
Monte Carlo methods, or Monte Carlo experiments, are a broad class of computational algorithms that rely on repeated random sampling to obtain numerical ...
An amortized approach to non-linear mixed-effects modeling based on neural posterior estimation ... Sarah Frank-Wolfe: Methods for Constrained Optimization with ...
12 Principles of Green Chemistry - American Chemical Society
Developed by Paul Anastas and John Warner in 1998, the following list outlines aa framework for making a greener chemical, process, or product.
Deterministic modeling: linear optimization with applications
Optimization models are also called Prescriptive or Normative models since they seek to find the best possible strategy for decision-maker. There are many ...
Effect of contrast media on CT bone density assessment - Nature
Identifying the optimal CT modality for BMD assessment can improve the rates of osteopenia and osteoporosis diagnosis. Although low-dose chest ...
What Is Data Analysis: Examples, Types, & Applications
Model Building: Depending on the objectives, apply appropriate data analysis methods, such as regression, clustering, or deep learning. Model ...
tensorflow/probability: Probabilistic reasoning and statistical ...
Optimizers ( tfp.optimizer ): Stochastic optimization methods ... A hierarchical normal model for exchangeable treatment effects. Hierarchical Linear Models.
Learning Curve Theory: Types, Formula, Examples (2024) - Whatfix
Doesn't account for multiple variables: Using the learning curve model ... using new medical technologies or treatment protocols with experience.