November 25, 2025International Journal of Scientific Research in Computer Science Engineering and Information TechnologyOpen Access

Optimizing Healthcare Workflows through Java-Powered Real-Time Data Analytics

View Full Paper

Ask AI

Bookmark

Authors

CGChinmay Mukeshbhai Gangani

Discussion

Member takes

Implication

This research develops a healthcare monitoring system using Bluetooth Low Energy and machine learning, improving patient safety and chronic illness management.

Key Points

Lower risks in healthcare delivery and improved patient safety are achieved through this approach.
A healthcare monitoring system utilizing Bluetooth Low Energy and machine learning enhances real-time data analysis.
Analysis of data streams and syndromic surveillance criteria increases the operational quality of HIT systems.
Effective integration of IoT and advanced analytics addresses key challenges in monitoring chronic illnesses.

Cite This Study

Chinmay Mukeshbhai Gangani (2023) studied this question.

synapsesocial.com/papers/692502ad87af00ed34ac1ccc https://doi.org/10.32628/cseit239095

View Full Paper

Ask AI

Bookmark

Implication

This research develops a healthcare monitoring system using Bluetooth Low Energy and machine learning, improving patient safety and chronic illness management.

Optimizing Healthcare Workflows through Java-Powered Real-Time Data Analytics

Discussion

Member takes

Implication

Key Points

Cite This Study

Optimizing Healthcare Workflows through Java-Powered Real-Time Data Analytics

Discussion

Member takes

Implication

Key Points

Cite This Study

Also Consider

Also Consider