Ensemble learning for disease prediction: A review
Machine learning models are used to create and enhance various disease prediction
frameworks. Ensemble learning is a machine learning technique that combines multiple …
frameworks. Ensemble learning is a machine learning technique that combines multiple …
A review on electronic health record text-mining for biomedical name entity recognition in healthcare domain
Biomedical-named entity recognition (bNER) is critical in biomedical informatics. It identifies
biomedical entities with special meanings, such as people, places, and organizations, as …
biomedical entities with special meanings, such as people, places, and organizations, as …
Machine learning based approaches for detecting COVID-19 using clinical text data
Technology advancements have a rapid effect on every field of life, be it medical field or any
other field. Artificial intelligence has shown the promising results in health care through its …
other field. Artificial intelligence has shown the promising results in health care through its …
Enhancing heart disease prediction accuracy through machine learning techniques and optimization
N Chandrasekhar, S Peddakrishna - Processes, 2023 - mdpi.com
In the medical domain, early identification of cardiovascular issues poses a significant
challenge. This study enhances heart disease prediction accuracy using machine learning …
challenge. This study enhances heart disease prediction accuracy using machine learning …
Diagnosis of diabetes mellitus using gradient boosting machine (LightGBM)
DD Rufo, TG Debelee, A Ibenthal, WG Negera - Diagnostics, 2021 - mdpi.com
Diabetes mellitus (DM) is a severe chronic disease that affects human health and has a high
prevalence worldwide. Research has shown that half of the diabetic people throughout the …
prevalence worldwide. Research has shown that half of the diabetic people throughout the …
[HTML][HTML] An ensemble machine learning approach for predicting type-II diabetes mellitus based on lifestyle indicators
Abstract Machine Learning (ML) is a branch of artificial intelligence that allows computers to
learn without being explicitly programmed. ML has been widely used in healthcare to predict …
learn without being explicitly programmed. ML has been widely used in healthcare to predict …
Performance analysis of machine learning based optimized feature selection approaches for breast cancer diagnosis
Healthcare systems around the world are facing huge challenges in responding to trends of
the rise of chronic diseases. The objective of our research study is the adaptation of Data …
the rise of chronic diseases. The objective of our research study is the adaptation of Data …
Detection of COVID-19 cases through X-ray images using hybrid deep neural network
Purpose The latest 2019 coronavirus (COVID-2019), which first appeared in December
2019 in Wuhan's city in China, rapidly spread around the world and became a pandemic. It …
2019 in Wuhan's city in China, rapidly spread around the world and became a pandemic. It …
Applications of Machine Learning in Viral Disease Diagnosis
Viral diseases are common and natural in human it spreads from animals and other
humans. It seeks to identify the proper, reliable, and effective disease detection as quickly as …
humans. It seeks to identify the proper, reliable, and effective disease detection as quickly as …
Identifying propaganda from online social networks during COVID-19 using machine learning techniques
COVID-19, affected the entire world because of its non-availability of vaccine. Due to social
distancing online social networks are massively used in pandemic times. Information is …
distancing online social networks are massively used in pandemic times. Information is …