[HTML][HTML] Reviewing the application of machine learning methods to model urban form indicators in planning decision support systems: Potential, issues and …
Modern cities dynamically face several challenges including digitalization, sustainability,
resilience and economic development. Urban planners and designers must develop urban …
resilience and economic development. Urban planners and designers must develop urban …
A survey on epistemic (model) uncertainty in supervised learning: Recent advances and applications
Quantifying the uncertainty of supervised learning models plays an important role in making
more reliable predictions. Epistemic uncertainty, which usually is due to insufficient …
more reliable predictions. Epistemic uncertainty, which usually is due to insufficient …
[HTML][HTML] An ensemble approach for classification and prediction of diabetes mellitus using soft voting classifier
Diabetes is a dreadful disease identified by escalated levels of glucose in the blood.
Machine learning algorithms help in identification and prediction of diabetes at an early …
Machine learning algorithms help in identification and prediction of diabetes at an early …
Machine learning applied to diagnosis of human diseases: A systematic review
N Caballé-Cervigón, JL Castillo-Sequera… - Applied Sciences, 2020 - mdpi.com
Human healthcare is one of the most important topics for society. It tries to find the correct
effective and robust disease detection as soon as possible to patients receipt the …
effective and robust disease detection as soon as possible to patients receipt the …
[HTML][HTML] IntelliHealth: a medical decision support application using a novel weighted multi-layer classifier ensemble framework
Accuracy plays a vital role in the medical field as it concerns with the life of an individual.
Extensive research has been conducted on disease classification and prediction using …
Extensive research has been conducted on disease classification and prediction using …
Type 2 diabetes with artificial intelligence machine learning: methods and evaluation
Diabetes, one of the top 10 causes of death worldwide, is associated with the interaction
between lifestyle, psychosocial, medical conditions, demographic, and genetic risk factors …
between lifestyle, psychosocial, medical conditions, demographic, and genetic risk factors …
[PDF][PDF] Analysis and prediction of diabetes diseases using machine learning algorithm: Ensemble approach
Machine learning techniques (MLT) are used to predict the medical datasets at an early
stage of safe human life. A huge medical datasets are accessible in different data …
stage of safe human life. A huge medical datasets are accessible in different data …
Classification extension based on IoT-big data analytic for smart environment monitoring and analytic in real-time system
R Arridha, S Sukaridhoto… - … Journal of Space …, 2017 - inderscienceonline.com
Monitoring water conditions in real-time is a critical mission to preserve the water ecosystem
in maritime and archipelagic countries, such as Indonesia that is relying on the wealth of …
in maritime and archipelagic countries, such as Indonesia that is relying on the wealth of …
Improvement in automated diagnosis of soft tissues tumors using machine learning
Soft Tissue Tumors (STT) are a form of sarcoma found in tissues that connect, support, and
surround body structures. Because of their shallow frequency in the body and their great …
surround body structures. Because of their shallow frequency in the body and their great …
HMV: A medical decision support framework using multi-layer classifiers for disease prediction
Decision support is a crucial function for decision makers in many industries. Typically,
Decision Support Systems (DSS) help decision-makers to gather and interpret information …
Decision Support Systems (DSS) help decision-makers to gather and interpret information …