Internet of Things(IoT) technology enables medical devices, sensors, and other healthcare-related equipment to connect and communicate with each other.This connectivity enables enhanced monitoring, data collecting, and analysis, resulting in enhanced patient outcomes and more effective healthcare delivery. However, with the increased use of connected devices, detecting and preventing Cyberattack is essential to protect sensitive patient information. To address this challenge, the article discusses the use of some machine learning algorithms, such as Logistic Regression(LR), Random Forest(RF), Gradient Boosting(GB), and Support Vector Machine(SVM), Naive Bayes(NB), K-Nearest Neighbour(KNN) to detect the attacks. The WUSTL EHMS 2020 data set was used to test these algorithms, resulting in the best accuracy. Overall, the article highlights the potential benefits of IoT technology and machine learning in healthcare while emphasizing the importance of data privacy and detecting attacks.