Smart Healthcare
Smart healthcare leverages artificial intelligence and the Internet of Things to improve healthcare delivery and patient outcomes, focusing on areas like accurate diagnosis, personalized treatment, and efficient resource management. Current research emphasizes the development and application of machine learning models, including convolutional neural networks, recurrent neural networks, and ensemble methods, often within federated learning frameworks to address data privacy concerns. This field is significant for its potential to enhance diagnostic accuracy, personalize interventions, improve medication adherence, and ultimately lead to more effective and efficient healthcare systems.
Papers
Towards Implementing Energy-aware Data-driven Intelligence for Smart Health Applications on Mobile Platforms
G. Dumindu Samaraweera, Hung Nguyen, Hadi Zanddizari, Behnam Zeinali, J. Morris Chang
iPAL: A Machine Learning Based Smart Healthcare Framework For Automatic Diagnosis Of Attention Deficit/Hyperactivity Disorder (ADHD)
Abhishek Sharma, Arpit Jain, Shubhangi Sharma, Ashutosh Gupta, Prateek Jain, Saraju P. Mohanty