Survey of machine learning algorithms for disease diagnostic

M Fatima, M Pasha - Journal of …, 2017 - geographical.openuniversityarchive …
In medical imaging, Computer Aided Diagnosis (CAD) is a rapidly growing dynamic area of
research. In recent years, significant attempts are made for the enhancement of computer …

[PDF][PDF] Educational data mining and analysis of students' academic performance using WEKA

S Hussain, NA Dahan, FM Ba-Alwib… - Indonesian Journal of …, 2018 - researchgate.net
In this competitive scenario of the educational system, the higher education institutes use
data mining tools and techniques for academic improvement of the student performance and …

Prediction of breast cancer using voting classifier technique

UK Kumar, MBS Nikhil… - 2017 IEEE international …, 2017 - ieeexplore.ieee.org
Breast cancer became one of the deadliest cancer in women. It occurs when the growth of
the cells in breast tissue become out of control. Cells are the building blocks for the organs …

A review on blood disease detection using artificial intelligence techniques

D Gaikwad, V Mahale… - 2024 IEEE International …, 2024 - ieeexplore.ieee.org
Patient's data is gathered during medical procedures in order to assist the doctor in making
an accurate diagnosis of the patient's health. This information may consist of straightforward …

HMV: A medical decision support framework using multi-layer classifiers for disease prediction

S Bashir, U Qamar, FH Khan, L Naseem - Journal of Computational …, 2016 - Elsevier
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 …

Computer-assisted frameworks for classification of liver, breast and blood neoplasias via neural networks: A survey based on medical images

A Brunetti, L Carnimeo, GF Trotta, V Bevilacqua - Neurocomputing, 2019 - Elsevier
Abstract Computer Aided Diagnosis (CAD) systems can support physicians in classifying
different kinds of breast cancer, liver cancer and blood tumours also revealed by images …

Hybrid swarm intelligence algorithms with ensemble machine learning for medical diagnosis

Q Al-Tashi, H Rais, SJ Abdulkadir - 2018 4th international …, 2018 - ieeexplore.ieee.org
Disease Diagnosis still an open problem in current research. The main characteristic of
diseases diagnostic model is that it helps physicians to make quick decisions and minimize …

Prediction of hepatitis disease using machine learning technique

VK Yarasuri, GK Indukuri… - … on I-SMAC (IoT in Social …, 2019 - ieeexplore.ieee.org
The objective of this work is to choose the best tool for diagnosis and detection of Hepatitis
as well as for the prediction of life expectancy of Hepatitis patients. In this work, a …

Ensemble method based predictive model for analyzing disease datasets: a predictive analysis approach

D Ramesh, YS Katheria - Health and Technology, 2019 - Springer
Medical datasets have attracted the research community for possible analysis and suitable
prediction, which helps the human to take proper precautions in preventing future diseases …

Diagnosis of liver disease induced by hepatitis virus using machine learning methods

MA Hafeez, A Imran, MI Khan, AH Khan… - 2022 8th …, 2022 - ieeexplore.ieee.org
Liver, the largest vital organ in the human body, helps in digestion, energy storage, and toxic
removal processes. Hepatitis A, B, C, fatty liver, cirrhosis, and liver cancer all cause swelling …