Edge AI for early detection of chronic diseases and the spread of infectious diseases: opportunities, challenges, and future directions

E Badidi - Future Internet, 2023 - mdpi.com
Edge AI, an interdisciplinary technology that enables distributed intelligence with edge
devices, is quickly becoming a critical component in early health prediction. Edge AI …

Identification and prediction of chronic diseases using machine learning approach

R Alanazi - Journal of Healthcare Engineering, 2022 - Wiley Online Library
Nowadays, humans face various diseases due to the current environmental condition and
their living habits. The identification and prediction of such diseases at their earlier stages …

[PDF][PDF] Multi Head Deep Neural Network Prediction Methodology for High-Risk Cardiovascular Disease on Diabetes Mellitus.

B Ramesh, K Lakshmanna - CMES-Computer Modeling in …, 2023 - cdn.techscience.cn
Major chronic diseases such as Cardiovascular Disease (CVD), diabetes, and cancer
impose a significant burden on people and healthcare systems around the globe. Recently …

Chronic Disease prediction using Machine Learning Techniques: A Survey

N Kumari, M Gautam - 2023 14th International Conference on …, 2023 - ieeexplore.ieee.org
In current era people are very much prone to the ChronicDisease because of the ambient
circumstances and lifestyle practices. Thus it became very vital task for doctors to predictit at …

Machine Learning-Based Approach for Early Detection and Prediction of Chronic Diseases

SS Shambharkar, PS Moon… - 2023 1st DMIHER …, 2023 - ieeexplore.ieee.org
It is essential to identify and predict certain diseases early on in order to stop them from
progressing. However, doctors frequently make mistakes when performing manual …

14 Application of

A Nag, AK Bairagi, A Dutta - Internet of Things and Big Data …, 2024 - books.google.com
The term Artificial Intelligence (AI) pertains to the theoretical ability of robots to per-form
cognitive functions that are commonly associated with human brains, including but not …

Improving Diagnostic Accuracy: A Deep Dive into Random Forest Optimization for Clinical Data

M Modak, M Jadhav, R Kadam… - 2024 3rd International …, 2024 - ieeexplore.ieee.org
The healthcare industry produces a large amount of patient data, which makes it possible to
use a variety of analytical techniques on a large dataset. A predictive system that can …

Application of Artificial Intelligence in the Diagnosis and Treatment of Cancer: A Comprehensive Review

A Nag, B Das, R Sill, AK Bairagi, A Dutta… - Internet of Things and Big … - taylorfrancis.com
Artificial Intelligence (AI) is a human-created technology that can mimic human cognitive
functions including reasoning and thinking. AI works well in medicine, health, agriculture …

[PDF][PDF] Machine Learning-Based Identification and Forecasting of Chronic Illnesses

M Sarada, R Suresh - researchgate.net
People today suffer from a wide range of illnesses as a result of their lifestyle choices and
the state of the environment. In order to stop such diseases from getting worse, it is crucial to …

Chronic Diseases Risk Prediction Model using Convolution Neural Network and SMOTE Model

K Gyatso, R Jayanthi, R Suchithra - NeuroQuantology, 2022 - search.proquest.com
Clinical judgments are typically reliant on the practitioners' experiences, with only a very
limited amount of support from data-centric analytic methods from medical databases. This …