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The NipahNipah virus is a lethal animal and human disease that originates in bats. The urgency in detecting and identifying the virus, driven by a desire to comprehend the efficacy of machine learningMachine learning, stems from the fact that the virus is lethal. From a medical standpoint, there is currently no vaccine or drug that can cure the NipahNipah virus. Machine learning algorithmsMachine learning algorithms play an essential role in the medical industry when using ML predictionsPrediction to identify and isolate viruses in critical and questionable situations. In order to determine if a patient has an infection with the NipahNipah virus, this method will provide numerical data. "Prevention is better than cure" when it comes to the NipahNipah virus, which does not yet have a vaccine. More and more, machine learningMachine learning techniques, such as decision treesDecision Tree (DT) and random forestsRandom Forest (RF), are being used to enhance the accuracy of models.

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Leverage Machine Learning to Infer Proof of the Nipah Influenza

  • 会议论文

  • 发表日期：

    2025年

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  • D. C. Shubhangi,
  • Baswaraj Gadgay,
  • S. Anita

摘要

The NipahNipah virus is a lethal animal and human disease that originates in bats. The urgency in detecting and identifying the virus, driven by a desire to comprehend the efficacy of machine learningMachine learning, stems from the fact that the virus is lethal. From a medical standpoint, there is currently no vaccine or drug that can cure the NipahNipah virus. Machine learning algorithmsMachine learning algorithms play an essential role in the medical industry when using ML predictionsPrediction to identify and isolate viruses in critical and questionable situations. In order to determine if a patient has an infection with the NipahNipah virus, this method will provide numerical data. "Prevention is better than cure" when it comes to the NipahNipah virus, which does not yet have a vaccine. More and more, machine learningMachine learning techniques, such as decision treesDecision Tree (DT) and random forestsRandom Forest (RF), are being used to enhance the accuracy of models.