The Significance of Machine Learning in Clinical Disease Diagnosis: A Review

The global need for effective disease diagnosis remains substantial, given the complexities of various disease mechanisms and diverse patient symptoms. To tackle these challenges, researchers, physicians, and patients are turning to machine learning (ML), an artificial intelligence (AI) discipline, to develop solutions. By leveraging sophisticated ML and AI methods, healthcare stakeholders gain enhanced diagnostic and treatment capabilities. However, there is a scarcity of research focused on ML algorithms for enhancing the accuracy and computational efficiency. This research investigates the capacity of machine learning algorithms to improve the transmission of heart rate data in time series healthcare metrics, concentrating particularly on optimizing accuracy and efficiency. By exploring various ML algorithms used in healthcare applications, the review presents the latest trends and approaches in ML-based disease diagnosis (MLBDD). The factors under consideration include the algorithm utilized, the types of diseases targeted, the data types employed, the applications, and the evaluation metrics. This review aims to shed light on the prospects of ML in healthcare, particularly in disease diagnosis. By analyzing the current literature, the study provides insights into state-of-the-art methodologies and their performance metrics.Comment: 8 page

A Comparative Study on Different Big Data Tools

Big data has long been the topic of fascination for computer science enthusiasts around the world, and has gained even more prominence in recent times with the continuous explosion of data resulting from the likes of social media and the quest for tech giants to gain access to deeper analysis. This paper discusses various tools in big data technology and conducts a comparison among them. Different tools namely Sqoop, Apache Flume, Apache Kafka, Hive, Spark and many more are included. Various datasets are used for the experiment and a comparative study is made to figure out which tool works faster and more efficiently over the others, and explains the reason behind this