Healthcare applications of artificial intelligence and analytics: a review and proposed framework

S Azzi, S Gagnon, A Ramirez, G Richards - Applied Sciences, 2020 - mdpi.com
Healthcare is considered as one of the most promising application areas for artificial
intelligence and analytics (AIA) just after the emergence of the latter. AI combined to …

A review on machine learning approaches in identification of pediatric epilepsy

MIB Ahmed, S Alotaibi, S Dash, M Nabil… - SN computer science, 2022 - Springer
Epilepsy is the second most common neurological disease after Alzheimer. It is a disorder of
the brain which results in recurrent seizures. Though the epilepsy in general is considered …

A multiple combined method for rebalancing medical data with class imbalances

YC Wang, CH Cheng - Computers in Biology and Medicine, 2021 - Elsevier
Most classification algorithms assume that classes are in a balanced state. However,
datasets with class imbalances are everywhere. The classes of actual medical datasets are …

A classification approach for predicting COVID-19 Patient's survival outcome with machine learning techniques

AA Osi, M Abdu, U Muhammad, A Ibrahim, LA Isma'il… - MedRxiv, 2020 - medrxiv.org
COVID-19 is an infectious disease discovered after the outbreak began in Wuhan, China, in
December 2019. COVID-19 is still becoming an increasing global threat to public health …

[PDF][PDF] A comparative analysis and predicting for breast cancer detection based on data mining models

SF Khorshid, AM Abdulazeez… - Asian Journal of Research …, 2021 - dl.safirdep.com
Breast cancer is one of the most common diseases among women, accounting for many
deaths each year. Even though cancer can be treated and cured in its early stages, many …

A review on the significance of body temperature interpretation for early infectious disease diagnosis

NID Zaman, YW Hau, MC Leong… - Artificial Intelligence …, 2023 - Springer
Infectious diseases have always been a serious discussion worldwide due to their disease
elevation leading to mortality. Although vaccination and prevention exist for this kind of …

Combining contextual neural networks for time series classification

AF Kamara, E Chen, Q Liu, Z Pan - Neurocomputing, 2020 - Elsevier
Ten years ago, linear models were applied in various domains. Before application of the
algorithms, several current studies extracted features presumed to represent parochial …

Data mining in medical laboratory service improves disease surveillance and quality healthcare

UM Obeta, OR Ejinaka, NS Etukudoh - Prognostic Models in Healthcare: AI …, 2022 - Springer
Day in day out, data are turned out in various medical laboratories which are adequately
documented and used for surveillance in various diseases of concern in public health …

Explainable artificial intelligence and machine learning algorithms for classification of thyroid disease

P Kumari, B Kaur, M Rakhra, A Deka, H Byeon… - Discover Applied …, 2024 - Springer
A common endocrine issue affecting millions globally is thyroid illness. For this ailment to be
effectively treated and managed, an early and accurate diagnosis is essential. Machine …

[PDF][PDF] Classification and cost benefit Analysis of Diabetes mellitus Dominance

N Sohail, R Jiadong, M Uba, M Irshad… - Int. J. Comput. Sci. Netw …, 2018 - researchgate.net
The aim of research work is towards the prevalence of diabetes mellitus to improve
classification accuracy and cost/benefit predictions on real-life dataset. This paper aims the …