Stark assessment of lifestyle based human disorders using data mining based learning techniques
Background: Medical informatics has observed an unrestrained growth in the database.
Latest advancements in the field of medical sciences have wiped out lots of critical diseases …
Latest advancements in the field of medical sciences have wiped out lots of critical diseases …
A novel approach to model dynamic flow interactions between storm sewer system and overland surface for different land covers in urban areas
In this study, we developed a novel approach to simulate dynamic flow interactions between
storm sewers and overland surface for different land covers in urban areas. The proposed …
storm sewers and overland surface for different land covers in urban areas. The proposed …
A classification system for diabetic patients with machine learning techniques
V Rawat, S Suryakant - International Journal of Mathematical …, 2019 - ifp.hal.science
Diabetes mellitus (DM) is a group of metallic disorder characterized by steep levels of blood
glucose prolonged over a time. It results the defection in insulin production or improper …
glucose prolonged over a time. It results the defection in insulin production or improper …
Machine learning algorithms for early diagnosis of diabetes mellitus: A comparative study
A huge majority of people all over the globe are coping with the devastating effects of
diabetes, and many of them are not being identified early enough. Diabetes has become …
diabetes, and many of them are not being identified early enough. Diabetes has become …
Performance evaluation of Levenberg-Marquardt technique in error reduction for diabetes condition classification
N Khan, D Gaurav, T Kandl - Procedia Computer Science, 2013 - Elsevier
This paper aims to provide a case study to classify diabetes medical condition amongst
patients. The study examines the performance of the Levenberg-Marquardt (LM) algorithm …
patients. The study examines the performance of the Levenberg-Marquardt (LM) algorithm …
A faster SVM classification technique for remote sensing images using reduced training samples
The support vector machine (SVM) has been used as an efficient tool in data mining tasks
during the last 2 decades. It is also used for supervised classification with reasonable …
during the last 2 decades. It is also used for supervised classification with reasonable …
A case study for the application of an operational two-dimensional real-time flooding forecasting system and smart water level gauges on roads in Tainan City, Taiwan
An operational two-dimensional real-time flood forecasting system has been developed to
prevent urban inundation in Taiwan, and it uses the Delft-FEWS (Flood Early Warning …
prevent urban inundation in Taiwan, and it uses the Delft-FEWS (Flood Early Warning …
[PDF][PDF] An alternative algorithm for classification large categorical dataset: k-mode clustering reduced support vector machine
SW Purnami, JM Zain, T Heriawan - International Journal of …, 2011 - academia.edu
The reduced support vector machine (RSVM) is extension method of smooth support vector
machine (SSVM) for handling computational difficulties as well as reduces the model …
machine (SSVM) for handling computational difficulties as well as reduces the model …
Linear discriminant analysis based genetic algorithm with generalized regression neural network–a hybrid expert system for diagnosis of diabetes
J Jayashree, SA Kumar - Programming and Computer Software, 2018 - Springer
Among the applications enabled by expert systems, disease diagnosis is a particularly
important one. Nowadays, diabetes is found to be a complex health issue in human life …
important one. Nowadays, diabetes is found to be a complex health issue in human life …
[PDF][PDF] Harnessing Ensemble in Machine Learning for Accurate Early Prediction and Prevention of Heart Disease
Cardiovascular diseases (CVDs) remain a significant global health concern, demanding
precise and early prediction methods for effective intervention. In this comprehensive study …
precise and early prediction methods for effective intervention. In this comprehensive study …