Timely prediction of diabetes by means of machine learning practices
RP Tripathi, M Sharma, AK Gupta, D Pandey… - Augmented Human …, 2023 - Springer
The quality and quantity of medical data produced by digital devices have improved
significantly in recent decades. This has led to cheap and easy data generation. There has …
significantly in recent decades. This has led to cheap and easy data generation. There has …
Smart healthcare systems: an IoT with fog computing based solution for healthcared
Due to the COVID-19 pandemic, the world has faced a noteworthy challenge in the rise of
the rate of morbidity and mortality among people, especially the old, aged patients. The risk …
the rate of morbidity and mortality among people, especially the old, aged patients. The risk …
Early Diagnosis of Diabetes: A Comparison of Machine Learning Methods.
MS Alzboon, MS Al-Batah… - … Journal of Online & …, 2023 - search.ebscohost.com
Detection and management of diabetes at an early stage is essential since it is rapidly
becoming a global health crisis in many countries. Predictions of diabetes using machine …
becoming a global health crisis in many countries. Predictions of diabetes using machine …
[PDF][PDF] SFFT-CapsNet: Stacked Fast Fourier Transform for Retina Optical Coherence Tomography Image Classification using Capsule Network
The work of the Ophthalmologist in manually detecting specific eye related disease is
challenging especially screening through large volume of dataset. Deep learning models …
challenging especially screening through large volume of dataset. Deep learning models …
Machine learning model for prediction of malaria in low and high endemic areas of Tanzania
M Mariki - 2023 - dspace.nm-aist.ac.tz
Presumptive treatment and self-medication with anti-malaria drugs is a common practice in
most limited resource settings that hinders proper management of malaria. However, these …
most limited resource settings that hinders proper management of malaria. However, these …