Counting Bloom filters are highly space-efficient with a small probability of false positives. Concurrent access to a Counting bloom filter can greatly increase its insertion and query throughput.

We propose a platform that connects Doctors, Insurance and Patients and in doing so provides them value that won’t be possible otherwise. We use the platform to store the longitudinal health record of the patient (with ...

Conventional data warehouse systems are implemented either on a multi-dimensional database or a relational database. While the earlier supports MOLAP operations, the other supports ROLAP operations. In this work, we used ...

Resource allocation is a problem that requires complex decision making. Our focus is to solve this problem in the healthcare sector using Reinforcement Learning. We propose an RL pipeline that starts with a sequential ...

Real-time systems are becoming more complex and open, thus increasing their development and verification costs. Although several static verification tools have been proposed over the last decades, they suffer from scalability ...

In an era marked by unprecedented data growth and pervasive digital influence, ensuring model privacy is imperative as machine learning models gain prominence in diverse domains like healthcare, finance, and business. ...

This study aims to enhance the accuracy of predicting the 30-day mortality rate among patients following their first heart attack by leveraging machine learning and deep learning techniques. The current cardiac risk ...

Neurodegenerative diseases pose a significant global health challenge, necessitating innovative approaches for drug discovery. This study explores the application of recurrent neural networks (RNNs) in the generation of ...

With improved technology, every user now generates huge amount of data that requires ever increasing amount of space to store it. It is not economical for the users to purchase new storage device every time. As a remedy ...

Machine Learning models are deployed in various tasks including image classification, malware detection, network intrusion detection, etc. But recent work has demonstrated that even state-of-the-art deep neural networks, ...