[HTML][HTML] Hybrid XGBoost model with hyperparameter tuning for prediction of liver disease with better accuracy
BACKGROUND Liver disease indicates any pathology that can harm or destroy the liver or
prevent it from normal functioning. The global community has recently witnessed an …
prevent it from normal functioning. The global community has recently witnessed an …
Application of machine learning for cardiovascular disease risk prediction
Cardiovascular diseases (CVDs) are a common cause of heart failure globally. The need to
explore possible ways to tackle the disease necessitated this study. The study designed a …
explore possible ways to tackle the disease necessitated this study. The study designed a …
A hybrid machine learning model for timely prediction of breast cancer
Breast cancer is one of the leading causes of untimely deaths among women in various
countries across the world. This can be attributed to many factors including late detection …
countries across the world. This can be attributed to many factors including late detection …
[HTML][HTML] Bootstrapping random forest and CHAID for prediction of white spot disease among shrimp farmers
Technology is playing an important role is healthcare particularly as it relates to disease
prevention and detection. This is evident in the COVID-19 era as different technologies were …
prevention and detection. This is evident in the COVID-19 era as different technologies were …
[HTML][HTML] Evaluation of IoT-Enabled hybrid model for genome sequence analysis of patients in healthcare 4.0
Genome sequence matching is vital for health analytics and treatment in healthcare 4.0. It
focuses on finding whether a given sequence resembles other sequences that can help …
focuses on finding whether a given sequence resembles other sequences that can help …
[HTML][HTML] Remote monitoring system using slow-fast deep convolution neural network model for identifying anti-social activities in surveillance applications
EM Onyema, S Balasubaramanian, C Iwendi… - Measurement …, 2023 - Elsevier
Remote monitoring is the process that monitors and observes information from a distance
utilizing sensors or electronic types of equipment. Remote monitoring is used in real-time …
utilizing sensors or electronic types of equipment. Remote monitoring is used in real-time …
[HTML][HTML] Heart disease risk prediction using deep learning techniques with feature augmentation
MT García-Ordás, M Bayón-Gutiérrez… - Multimedia Tools and …, 2023 - Springer
Cardiovascular diseases state as one of the greatest risks of death for the general
population. Late detection in heart diseases highly conditions the chances of survival for …
population. Late detection in heart diseases highly conditions the chances of survival for …
Opportunities and challenges for the application of artificial intelligence paradigms into the management of endemic viral infections: The example of Chronic Hepatitis …
Despite the advent of direct‐acting antiviral agents (DAAs) as a definitive therapy for chronic
hepatitis C virus (HCV) infection, the burden of the disease remains globally elevated. The …
hepatitis C virus (HCV) infection, the burden of the disease remains globally elevated. The …
Artificial intelligence-based teleopthalmology application for diagnosis of diabetics retinopathy
Diabetic Retinopathy (DR) is one of the leading causes of blindness for people who have
diabetes in the world. However, early detection of this disease can essentially decrease its …
diabetes in the world. However, early detection of this disease can essentially decrease its …
[HTML][HTML] A risk prediction model for type 2 diabetes mellitus complicated with retinopathy based on machine learning and its application in health management
H Pan, J Sun, X Luo, H Ai, J Zeng, R Shi… - Frontiers in …, 2023 - frontiersin.org
Objective This study aimed to establish a risk prediction model for diabetic retinopathy (DR)
in the Chinese type 2 diabetes mellitus (T2DM) population using few inspection indicators …
in the Chinese type 2 diabetes mellitus (T2DM) population using few inspection indicators …