Fake News Management in Healthcare

Ciora, Radu Adrian; Cioca, Adriana L.

doi:10.1109/ehb52898.2021.9657578

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2022

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“…Ciora and Cioca [15] is another successful research on fake news detection in healthcare. Their research articles showed 70% accuracy achieved by using the KNN-BSA-based machine learning algorithms.…”

Section: Literature Reviewmentioning

confidence: 99%

Fake News Detection in the Medical Field Using Machine Learning Techniques

Murugesan¹,

Pachamuthu²

2022

IJSSE

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In today's world, fake news is the biggest and most challenging problem in the natural world environment. This type of fake news will create many problems in society, especially in the medical field. This research aims to detect automatic phoney news in the news. The following machine learning algorithm will help us to see phoney medical information based on dataset 1. KNN, 2. Naive Bayes, 3. Support Vector Machine, 4. BERT and 5. Decision tree, but the Decision tree will provide better accuracy. Findings: Performance measures such as accuracy, precision, recall, and f1-score showed 98.5% accuracy of our proposed Adaboost & Decision Tree algorithm. In this research work, we introduced and implemented the Proposed Ensembling (Adaboost & Decision tree) and achieved better accuracy. We collected and trained the dataset to identify misinformation in the medical area.

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Section: Literature Reviewmentioning

confidence: 99%