Impact of dataset size on classification performance: an empirical evaluation in the medical domain

A Althnian, D AlSaeed, H Al-Baity, A Samha, AB Dris… - Applied Sciences, 2021 - mdpi.com
Dataset size is considered a major concern in the medical domain, where lack of data is a
common occurrence. This study aims to investigate the impact of dataset size on the overall …

Finding an accurate early forecasting model from small dataset: A case of 2019-ncov novel coronavirus outbreak

SJ Fong, G Li, N Dey, RG Crespo… - arXiv preprint arXiv …, 2020 - arxiv.org
Epidemic is a rapid and wide spread of infectious disease threatening many lives and
economy damages. It is important to fore-tell the epidemic lifetime so to decide on timely and …

Handling a small dataset problem in prediction model by employ artificial data generation approach: A review

MA Lateh, AK Muda, ZIM Yusof… - Journal of Physics …, 2017 - iopscience.iop.org
The emerging era of big data for past few years has led to large and complex data which
needed faster and better decision making. However, the small dataset problems still arise in …

Student data mining solution–knowledge management system related to higher education institutions

S Natek, M Zwilling - Expert systems with applications, 2014 - Elsevier
Higher education institutions (HEIs) are often curious whether students will be successful or
not during their study. Before or during their courses the academic institutions try to estimate …

[HTML][HTML] A new cluster-based oversampling method for improving survival prediction of hepatocellular carcinoma patients

MS Santos, PH Abreu, PJ García-Laencina… - Journal of biomedical …, 2015 - Elsevier
Liver cancer is the sixth most frequently diagnosed cancer and, particularly, Hepatocellular
Carcinoma (HCC) represents more than 90% of primary liver cancers. Clinicians assess …

Data‐driven estimation of nitric oxide emissions from global soils based on dominant vegetation covers

X Tian, Y Yin, K He, R Qiu, J Cong, Z Wang… - Global Change …, 2023 - Wiley Online Library
Soils are a major source of global nitric oxide (NO) emissions. However, estimates of soil NO
emissions have large uncertainties due to limited observations and multifactorial impacts …

[HTML][HTML] Accuracy of machine learning algorithms for the assessment of upper-limb motor impairments in patients with post-stroke hemiparesis: A systematic review …

JF Ambros-Antemate, A Reyes-Flores… - … in Clinical and …, 2022 - advances.umw.edu.pl
Background. The assessment of motor function is vital in post-stroke rehabilitation protocols,
and it is imperative to obtain an objective and quantitative measurement of motor function …

[PDF][PDF] Intelligent forecasting model of COVID-19 novel coronavirus outbreak empowered with deep extreme learning machine

MA Khan, S Abbas, KM Khan… - … , Materials & Continua, 2020 - academia.edu
An epidemic is a quick and widespread disease that threatens many lives and damages the
economy. The epidemic lifetime should be accurate so that timely and remedial steps are …

Modelling and Simulation of COVID-19 Outbreak Prediction Using Supervised Machine Learning.

R Zagrouba, MA Khan, MA Saleem… - Computers …, 2021 - search.ebscohost.com
Abstract Novel Coronavirus-19 (COVID-19) is a newer type of coronavirus that has not been
formally detected in humans. It is established that this disease often affects people of …

Using data mining to predict instructor performance

AM Ahmed, A Rizaner, AH Ulusoy - Procedia Computer Science, 2016 - Elsevier
During these decades, data mining has become one of the effective tools for data analysis
and knowledge management system, so that there are many areas which adapted data …