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

Machines01:19

Machines

573
Machines are complex structures consisting of movable, pin-connected multi-force members that work together to transmit forces. One example of a machine is the cutting plier, which is used to cut wires by applying forces to its handles. When equal and opposite forces are exerted on the handles of the cutting plier, they cause the cutting edges to come together and apply equal and opposite reaction forces on the wire, which are greater than the applied forces.
A free-body diagram of the...
573
Machines: Problem Solving II01:30

Machines: Problem Solving II

661
Machines are complex structures consisting of movable, pin-connected multi-force members that work together to transmit forces. Consider a lifting tong carrying a 100 kg load. It comprises movable sections DAF and CBG linked together with member AB.
661
Machines: Problem Solving I01:22

Machines: Problem Solving I

709
A toggle clamp is a mechanical device commonly used for holding and clamping objects in various applications, such as woodworking, metalworking, and assembly operations. Consider a toggle clamp subjected to a force of 200 N at the handle. The vertical clamping force can be calculated, provided the dimensions of the toggle clamp are known.
The toggle clamp system is a machine structure consisting of movable, pin-connected multi-force members that form a stabilized system to transmit forces. The...
709
Avoidance Learning and Learned Helplessness01:14

Avoidance Learning and Learned Helplessness

2.6K
Avoidance learning and learned helplessness are critical concepts in understanding behavioral responses to negative stimuli.
Avoidance learning occurs when an organism learns that a specific behavior can prevent an unpleasant outcome. For example, a student who receives a bad grade may start studying harder to avoid future poor grades. This behavior persists even when the negative outcome is no longer present. Avoidance learning is powerful because it maintains behavior in the absence of the...
2.6K
Sequence Networks of Rotating Machines01:24

Sequence Networks of Rotating Machines

486
A Y-connected synchronous generator, grounded through a neutral impedance, is designed to produce balanced internal phase voltages with only positive-sequence components. The generator's sequence networks include a source voltage that is exclusively in the positive-sequence network. The sequence components of line-to-ground voltages at the generator terminals illustrate this configuration.
Zero-sequence current induces a voltage drop across the generator's neutral impedance and other...
486
Simplified Synchronous Machine Model01:30

Simplified Synchronous Machine Model

769
The Synchronous Machine Model is a fundamental tool in analyzing and ensuring the transient stability of power systems. This model simplifies the representation of a synchronous machine under balanced three-phase positive-sequence conditions, assuming constant excitation and ignoring losses and saturation. The model is pivotal for understanding the behavior of synchronous generators connected to a power grid, particularly during transient events.
In this model, each generator is connected to a...
769

You might also read

Related Articles

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

Sort by
Same author

Clusters of Anthropometric Features in Colorectal Cancer Patients with Synchronous Metastases and Their Association with Overall Survival and RAS Mutation.

Journal of gastrointestinal cancer·2026
Same author

Reanimation of Stored Tissue Biopsies: A Functional Study and Translational Approach.

International journal of molecular sciences·2026
Same author

Human miRNAs in Cancer: Statistical Trends and Cross Kingdom Approach.

International journal of molecular sciences·2025
Same author

Leveraging knowledge for explainable AI in personalized cancer treatment: challenges and future directions.

Frontiers in digital health·2025
Same author

Psychometric Properties of the Self Care Oral Anticancer Agents Index (SCOAAI).

Seminars in oncology nursing·2025
Same author

Plant miRNAs for Improved Gene Regulation in a Wide Range of Human Cancers.

Current issues in molecular biology·2025

Related Experiment Video

Updated: Jan 27, 2026

Studying Triple Negative Breast Cancer Using Orthotopic Breast Cancer Model
09:29

Studying Triple Negative Breast Cancer Using Orthotopic Breast Cancer Model

Published on: March 20, 2020

18.8K

Breast Cancer Prognosis Using a Machine Learning Approach.

Patrizia Ferroni1,2, Fabio M Zanzotto3, Silvia Riondino4,5

  • 1BioBIM (InterInstitutional Multidisciplinary Biobank), IRCCS San Raffaele Pisana, Via di Val Cannuta 247, 00166 Rome, Italy. patrizia.ferroni@sanraffaele.it.

Cancers
|March 15, 2019
PubMed
Summary
This summary is machine-generated.

Machine learning models can predict breast cancer patient outcomes using routine data. This decision support system shows high accuracy in identifying high-risk patients, paving the way for personalized medicine.

Keywords:
artificial intelligencebreast cancer prognosisdecision support systemsmachine learning

More Related Videos

Constructing and Visualizing Models using Mime-based Machine-learning Framework
06:19

Constructing and Visualizing Models using Mime-based Machine-learning Framework

Published on: July 22, 2025

2.4K
Orthotopic Transplantation of Breast Tumors as Preclinical Models for Breast Cancer
07:45

Orthotopic Transplantation of Breast Tumors as Preclinical Models for Breast Cancer

Published on: May 18, 2020

7.0K

Related Experiment Videos

Last Updated: Jan 27, 2026

Studying Triple Negative Breast Cancer Using Orthotopic Breast Cancer Model
09:29

Studying Triple Negative Breast Cancer Using Orthotopic Breast Cancer Model

Published on: March 20, 2020

18.8K
Constructing and Visualizing Models using Mime-based Machine-learning Framework
06:19

Constructing and Visualizing Models using Mime-based Machine-learning Framework

Published on: July 22, 2025

2.4K
Orthotopic Transplantation of Breast Tumors as Preclinical Models for Breast Cancer
07:45

Orthotopic Transplantation of Breast Tumors as Preclinical Models for Breast Cancer

Published on: May 18, 2020

7.0K

Area of Science:

  • Oncology
  • Biomedical Informatics
  • Machine Learning

Background:

  • Machine learning (ML) is emerging for cancer prognosis.
  • Predicting individual cancer patient outcomes is crucial for treatment.

Purpose of the Study:

  • To evaluate an ML-based decision support system (DSS) combined with random optimization (RO).
  • To extract prognostic information from routinely collected breast cancer patient data.

Main Methods:

  • Developed a DSS model using training data (n=318).
  • Applied random optimization to extract prognostic features.
  • Evaluated model performance on a testing set (n=136).

Main Results:

  • Achieved a C-index of 0.84 for progression-free survival.
  • Demonstrated 86% accuracy in patient outcome prediction.
  • Successfully stratified patients into low- and high-risk groups (HR=10.9, p<0.0001).

Conclusions:

  • ML algorithms and RO models integrated with EHR data can yield valuable prognostic information.
  • This approach has the potential to advance personalized cancer medicine.
  • Further validation in multicenter prospective studies is recommended.