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Synapse
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Synapse
January 14, 20260 citations

Retraction Notice: Machine learning based heart disease prediction system

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SKS. KanimozhiNSN. Sivanandan

Key Points

  • The aim is to address and retract fraudulent research related to machine learning and heart disease.
  • Identification of fraudulent research published in scientific journals.
  • Review of publication integrity through whistleblower reports and external screening tools.
  • Implementation of measures to prevent future occurrences.
  • The article was retracted due to being identified as nonsensical and potentially computer-generated.
  • Fraudulent research practices highlighted serious publication ethics concerns.
  • Additional preventive measures have been established by the publisher.

Abstract

We take a zero tolerance to any situation where fraudulent research is published in our journals. As a result, this article has been retracted by the Publisher because it is suspected to be a nonsensical computer-generated publication with a number of tortured phrases and irrelevant references. Additional measures have been implemented to prevent these issues from reoccurring. EDP Sciences is extremely grateful to anonymous whistleblowers and the Problematic Paper Screener 1 for bringing this case to our attention for further investigations.

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Cite This Study

Kanimozhi et al. (2026) studied this question.

synapsesocial.com/papers/696719a7c0d1e3cfbfce8f98https://doi.org/10.1051/e3sconf/202449103026/pdf
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Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Retraction Notice: Enhanced machine learning models for predicting breast cancer: healthcare system2026
  2. 2Retraction Notice: Automated lung disease detection, classification and prediction using RNN framework2026
  3. 3Retraction Notice: Applying machine learning to soil analysis for accurate farming2026
  4. 4Retraction Notice: Hate Classifier for Social Media Platform Using Tree LSTM2026
  5. 5Retraction Notice: Enhancing Sentiment Analysis Accuracy by Optimizing Hyper-parameters of SVM and Logistic Regression Models2026