Artificial intelligence-based ensemble learning model for prediction of hepatitis C disease
Machine learning algorithms are excellent techniques to develop prediction models to
enhance response and efficiency in the health sector. It is the greatest approach to avoid the …
enhance response and efficiency in the health sector. It is the greatest approach to avoid the …
[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 …
Text‐Based Emotion Recognition Using Deep Learning Approach
Sentiment analysis is a method to identify people's attitudes, sentiments, and emotions
towards a given goal, such as people, activities, organizations, services, subjects, and …
towards a given goal, such as people, activities, organizations, services, subjects, and …
Enabling artificial intelligence of things (AIoT) healthcare architectures and listing security issues
A significant study has been undertaken in the areas of health care and administration of
cutting‐edge artificial intelligence (AI) technologies throughout the previous decade …
cutting‐edge artificial intelligence (AI) technologies throughout the previous decade …
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 …
IntOPMICM: intelligent medical image size reduction model
Due to the increasing number of medical imaging images being utilized for the diagnosis
and treatment of diseases, lossy or improper image compression has become more …
and treatment of diseases, lossy or improper image compression has become more …
Bootstrap** 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 …
Recent advances in machine learning assisted hydrogel flexible sensing
S Zhou, D Song, L Pu, W Xu - Zeitschrift für anorganische und …, 2024 - Wiley Online Library
Hydrogel flexible sensors are widely used in wearable devices, health care, intelligent
robots and other fields due to their excellent flexibility, biocompatibility and high sensitivity …
robots and other fields due to their excellent flexibility, biocompatibility and high sensitivity …
Hyper-parameter tuned deep learning approach for effective human monkeypox disease detection
Human monkeypox is a very unusual virus that can devastate society. Early identification
and diagnosis are essential to treat and manage an illness effectively. Human monkeypox …
and diagnosis are essential to treat and manage an illness effectively. Human monkeypox …
Improved energy efficiency using adaptive ant colony distributed intelligent based clustering in wireless sensor networks
Optimization algorithms have come a long way in the last several decades, with the goal of
reducing energy consumption and minimizing interference with primary users during data …
reducing energy consumption and minimizing interference with primary users during data …