Malik Sajjad Ahmed Nadeem
Orcid: 0000-0002-4181-329X
According to our database1,
Malik Sajjad Ahmed Nadeem
authored at least 14 papers
between 2010 and 2024.
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Bibliography
2024
Scale based entropy measures and deep learning methods for analyzing the dynamical characteristics of cardiorespiratory control system in COVID-19 subjects during and after recovery.
Comput. Biol. Medicine, March, 2024
2022
Analysis of Proposed and Traditional Boosting Algorithm with Standalone Classification Methods for Classifying Gene Expresssion Microarray Data Using a Reject Option.
Appl. Artif. Intell., December, 2022
2020
Extraction of Dynamical Information and Classification of Heart Rate Variability Signals Using Scale Based Permutation Entropy Measures.
Traitement du Signal, 2020
J. Intell. Inf. Syst., 2020
Machine Learning Based Cost Effective Electricity Load Forecasting Model Using Correlated Meteorological Parameters.
IEEE Access, 2020
A Cooperative Binary-Clustering Framework Based on Majority Voting for Twitter Sentiment Analysis.
IEEE Access, 2020
2019
A Novel Phase Space Reconstruction- (PSR-) Based Predictive Algorithm to Forecast Atmospheric Particulate Matter Concentration.
Sci. Program., 2019
On the Feature Selection Methods and Reject Option Classifiers for Robust Cancer Prediction.
IEEE Access, 2019
Analyzing the Dynamics of Lung Cancer Imaging Data Using Refined Fuzzy Entropy Methods by Extracting Different Features.
IEEE Access, 2019
Class Association and Attribute Relevancy Based Imputation Algorithm to Reduce Twitter Data for Optimal Sentiment Analysis.
IEEE Access, 2019
Accuracy Rejection Normalized-Cost Curves (ARNCCs): A Novel 3-Dimensional Framework for Robust Classification.
IEEE Access, 2019
2018
Spatial Wavelet-Based Coherence and Coupling in EEG Signals With Eye Open and Closed During Resting State.
IEEE Access, 2018
2015
Proceedings of the 13th International Conference on Frontiers of Information Technology, 2015
2010
Accuracy-Rejection Curves (ARCs) for Comparing Classification Methods with a Reject Option.
Proceedings of the third International Workshop on Machine Learning in Systems Biology, 2010