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  1. Home
  2. /Repositories
  3. /1010sb/breast_cancer_prediction
Read original ↗
repoGitLabTrust 82 · PrimaryPublished 6d agoLive · 4d ago

1010sb/breast_cancer_prediction

This project aims to develop a breast cancer prediction system using machine learning algorithms. By analyzing a breast cancer dataset, various models such as logistic regression, support vector machines, decision trees, and random forests were implemented and evaluated.

Lineage graph

Paper → model → repo connections mined from source citations (Tier-1 exact match).

Why these links exist

Every edge carries a method, confidence, and the source snippet that justified it — so bad links are debuggable.

  • PossiblePossibly related (embedding) · 68%Machine Learning Predicts Survival in Breast Cancer Bone Metastasis - EMJ →
  • PossiblePossibly related (embedding) · 66%Patient-Reported Outcomes, Machine Learning May Predict Breast Cancer Recurrence Earlier - Pharmacy Times →
  • PossiblePossibly related (embedding) · 64%Breast cancer detection and classification via a robust deep learning approach - Nature →
  • PossiblePossibly related (embedding) · 54%Diabetes Prediction with Machine Learning: Improving Healthcare Outcomes - springerprofessional.de →
  • PossiblePossibly related (embedding) · 54%Machine Learning Model Accurately Identifies Risk for Postcardiotomy Cardiogenic Shock - Anesthesiology News →
  • PossiblePossibly related (embedding) · 58%Machine learning survival models for colorectal cancer: advantages of random survival forests over classification algorithms - Nature →

Covers

newsMachine Learning Predicts Survival in Breast Cancer Bone Metastasis - EMJnewsPatient-Reported Outcomes, Machine Learning May Predict Breast Cancer Recurrence Earlier - Pharmacy TimesnewsBreast cancer detection and classification via a robust deep learning approach - NaturenewsDiabetes Prediction with Machine Learning: Improving Healthcare Outcomes - springerprofessional.denewsMachine Learning Model Accurately Identifies Risk for Postcardiotomy Cardiogenic Shock - Anesthesiology News

Covers (incoming)

newsMachine learning survival models for colorectal cancer: advantages of random survival forests over classification algorithms - Nature

Related across the graph

newsMachine learning survival models for colorectal cancer: advantages of random survival forests over classification algorithms - NaturenewsMachine Learning Predicts Survival in Breast Cancer Bone Metastasis - EMJnewsBreast cancer detection and classification via a robust deep learning approach - NaturenewsMachine Learning Model Accurately Identifies Risk for Postcardiotomy Cardiogenic Shock - Anesthesiology NewsnewsDiabetes Prediction with Machine Learning: Improving Healthcare Outcomes - springerprofessional.denewsPatient-Reported Outcomes, Machine Learning May Predict Breast Cancer Recurrence Earlier - Pharmacy Times
Knowledge path·NMachine learning survival models for colorectal cancer: advantages of random survival forests over classification algorithms - Nature→NMachine Learning Predicts Survival in Breast Cancer Bone Metastasis - EMJ→NBreast cancer detection and classification via a robust deep learning approach - Nature→R1010sb/breast_cancer_prediction

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gitlabopen-source

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Graph trust82Primary