Machine learning techniques in adaptive and personalized systems for health and wellness

O Oyebode, J Fowles, D Steeves… - International Journal of …, 2023 - Taylor & Francis
Traditional health systems mostly rely on rules created by experts to offer adaptive
interventions to patients. However, with recent advances in artificial intelligence (AI) and …

Diabetes disease prediction using machine learning on big data of healthcare

A Mir, SN Dhage - 2018 fourth international conference on …, 2018 - ieeexplore.ieee.org
Healthcare domain is a very prominent research field with rapid technological advancement
and increasing data day by day. In order to deal with large volume of healthcare data we …

[PDF][PDF] The effect of gamma value on support vector machine performance with different kernels

IS Al-Mejibli, JK Alwan, DH Abd - Int. J. Electr. Comput. Eng, 2020 - academia.edu
Currently, the support vector machine (SVM) regarded as one of supervised machine
learning algorithm that provides analysis of data for classification and regression. This …

Classifying political arabic articles using support vector machine with different feature extraction

DH Abd, AT Sadiq, AR Abbas - … on Applied Computing to Support Industry …, 2019 - Springer
In the recent years, the number of web logs, and the amount of opinionated data on the
World Wide Web, have been grown substantially. The ability to determine the political …

Political articles categorization based on different naïve bayes models

DH Abd, AT Sadiq, AR Abbas - … on applied computing to support industry …, 2019 - Springer
Sentiment analysis plays an important role in most of human activities and has a significant
impact on our behaviours. With the development and use of web technology, there is a huge …

Performance evaluation of kernels in support vector machine

IS Al-Mejibli, DH Abd, JK Alwan… - 2018 1st Annual …, 2018 - ieeexplore.ieee.org
Recently, the Support Vector Machine (SVM) algorithm becomes very common technique
that developed for pattern classification. This technique has been employed in many fields …

Monitoring system for sickle cell disease patients by using supervised machine learning

DH Abd, IS Al-Mejibli - … in IT and Communication Science and …, 2017 - ieeexplore.ieee.org
Recently, the need for a real-time healthcare monitoring system that able to offer remote and
personal health-care services has increased. The patients with Sickle Cell Disease (SCD) …

[PDF][PDF] Mushroom diagnosis assistance system based on machine learning by using mobile devices

IS Al-Mejibli, DH Abd - Journal of Al-Qadisiyah for computer science and …, 2017 - iasj.net
Picking the wild mushrooms from the wild and forests for food purpose or for fun has become
a public issue within the last years because many types of mushrooms are poisonous …

Big Data and Machine Learning in Healthcare: Tools & Challenges

K Pahwa, S Chauhan - 2021 3rd International Conference on …, 2021 - ieeexplore.ieee.org
Normally healthcare is said to be information rich and to extract hidden data from such
information-rich industry is difficult. It becomes necessary for healthcare informatics to deal …

Ant lion optimization based medical data classification using modified neuro fuzzy classifier

B Tarle, S Jena - Wireless Personal Communications, 2021 - Springer
The progression of converting depiction of medical analysis and measures into widespread
medical code numbers is known as medical classification. According to the conclusion of …