Results 41 to 50 of about 13,178 (146)

Identification of Clinically Relevant HIV Vif Protein Motif Mutations through Machine Learning and Undersampling

Cells, 2023
Human Immunodeficiency virus (HIV) and its clinical entity, the Acquired Immunodeficiency Syndrome (AIDS) continue to represent an important health burden worldwide.
José Salomón Altamirano-Flores, Luis Ángel Alvarado-Hernández, Juan Carlos Cuevas-Tello, Peter Tino, Sandra E. Guerra-Palomares, Christian A. Garcia-Sepulveda   +5 more
doaj   +1 more source

Comparison of Support Vector Machine and Decision Tree Algorithm Performance with Undersampling Approach in Predicting Heart Disease Based on Lifestyle

Journal of Applied Informatics and Computing
Heart disease is one of the leading causes of death in the world with risk factors such as atherosclerosis, high blood pressure, and smoking. Early diagnosis is essential to reduce mortality and improve patients' quality of life. This study evaluates the
Gusti Ayu Putu Febriyanti, Anna Baita
doaj   +1 more source

Data Reduction in Phase-Sensitive OTDR with Ultra-Low Sampling Resolution and Undersampling Techniques

Sensors, 2022
Data storage is a problem that cannot be ignored in the long-term monitoring of a phase-sensitive optical time-domain reflectometry (Φ-OTDR) system. In this paper, we proposed a data-reduction approach for heterodyne Φ-OTDR using an ultra-low sampling ...
Feihong Yu, Liyang Shao, Shuaiqi Liu, Weijie Xu, Dongrui Xiao, Huanhuan Liu, Perry Ping Shum   +6 more
doaj   +1 more source

An Efficient and Robust Frequency Estimator Dealing With Short-Observation Under-Sampled Waveforms

IEEE Access, 2018
Frequency estimation of a noisy signal in under-sampled conditions is a challenging problem, which has proved to be effectively solved by Chinese remainder theorem (CRT).
Xiangdong Huang, Mengkai Yang, Mingzhuo Liu, Lin Yang   +3 more
doaj   +1 more source

Reliable Parkinson’s Disease Detection by Analyzing Handwritten Drawings: Construction of an Unbiased Cascaded Learning System Based on Feature Selection and Adaptive Boosting Model

IEEE Access, 2019
Parkinson's disease (PD) is the second most common neurodegenerative disease of central nervous system (CNS). Till now, there is no definitive clinical examination that can diagnose a PD patient.
Liaqat Ali, Ce Zhu, Noorbakhsh Amiri Golilarz, Ashir Javeed, Mingyi Zhou, Yipeng Liu   +5 more
doaj   +1 more source

An Empirical Analysis of Crash Injury Severity Among Young Drivers in England: Accounting for Data Imbalance

Applied Sciences
Crash data analysis is key to improving road safety, but imbalanced data challenges accurate predictions for severe crashes, often leading to biased outcomes. This study investigates crash severity among young drivers (aged 17–24) in England, using crash
Amirhossein Taheri, Kevin Switala, Grigorios Fountas, Abbas Sheykhfard, Nima Dadashzadeh, Steffen Müller   +5 more
doaj   +1 more source

Reconstruction of Self-Sparse 2D NMR Spectra from Undersampled Data in the Indirect Dimension

Sensors, 2011
Reducing the acquisition time for two-dimensional nuclear magnetic resonance (2D NMR) spectra is important. One way to achieve this goal is reducing the acquired data.
Zhong Chen, Shuhui Cai, Xue Cao, Di Guo, Xiaobo Qu   +4 more
doaj   +1 more source

From chaos to randomness via geometric undersampling [PDF]

ESAIM: Proceedings and Surveys, 2014
We propose a new mechanism for undersampling chaotic numbers obtained by the ring coupling of one-dimensional maps. In the case of 2 coupled maps this mechanism allows the building of a PRNG which passes all NIST Test. This new geometric undersampling is very effective for generating 2 parallel streams of pseudo-random numbers, as we show, computing ...
Lozi, René, Taralova, Ina
openaire   +4 more sources

Maximal Information Coefficient-Based Undersampling Method for Highly-Imbalanced Learning

IEEE Access
Learning from highly-imbalanced datasets is still a big challenge in the field of machine learning because models created by general learning algorithms are weak in recognizing the samples from the minority class correctly.
Haiou Qin
doaj   +1 more source

EKMGS: A HYBRID CLASS BALANCING METHOD FOR MEDICAL DATA PROCESSING

Scientific Journal of Astana IT University
The field of medicine is witnessing rapid development of AI, highlighting the importance of proper data processing. However, when working with medical data, there is a problem of class imbalance, where the amount of data about healthy patients ...
Zholdas Buribayev, Saida Shaikalamova, Ainur Yerkos, Rustem Imanbek   +3 more
doaj   +1 more source