Unmasking Healthcare Misinformation RNN Based Detection

In today's world, internet has opened up a box full of data to users. In field of healthcare the authenticity of data is very crucial for patient well-being and well-informed decision making. This research involves the use of neural networks towards the objective of identifying misinformation in healthcare domain. The study emphasizes the importance of precise and diverse data to build a model capable of unmasking misinformation in healthcare domain. The primary goal is to offer a robust method for evaluating the veracity of health information. Through a comparative analysis of machine learning and deep learning models, the research concludes that the RNN deep learning model excels in identifying false healthcare information. The study showcases the superiority of deep learning models over traditional machine learning approaches, underscoring the need for enhancing datasets to enhance the accuracy and relevance of the detection system, due to ever changing landscape of healthcare data.