… the topic of disease prediction utilizing various machine learning approaches and algorithms
… We will examine the accuracy of various diseases predicted using our suggested system in …

… Deep Learning (DL), a subfield of Machine learning (ML) techniques are explored in this
context so that future predictions can … Recurrent Neural Network (RNN) [8] follows deep learning …

… A machine learning technique discovers illness which helps clinical staffs in sickness
analysis and offers dependable, powerful, and quick reaction just as diminishes the danger of …

… (IoT) and Machine Learning (ML) into agricultural systems. IoT devices can be deployed in
… These insights can help farmers optimize irrigation schedules, predict crop diseases, detect …

… to identify diseases using machine learning techniques is identified and here in our study
we gave a solution for the unavailability. In the process of identifying the diseases also the CNN…

… , a machine learning model is used to develop a model that is used for tuberculosis prediction.
… understanding of the disease. Continued advancements can lead to. The future scope of …

… , such as forecasting, growth prediction and prediction using … learning also solves classification
related problems such as … analyzed various Machine Learning tools for predicting various …

… machine learning (ML) models and ensemble learning … As a result, this method can be used
to address the problems with … In order to predict the accuracy of loan approval status for an …

… Communication Problems: Poor communication or a breakdown in communication
between spouses is a common cause of marital problems and, eventually, divorce. …

… prediction models by hybridizing machine learning technologies. This research shows the
present status of machine learning models for flood prediction … the rice disease prediction. This …