Salem A. Alyami

3.2k total citations · 2 hit papers
92 papers, 1.9k citations indexed

About

Salem A. Alyami is a scholar working on Statistics and Probability, Statistics, Probability and Uncertainty and Artificial Intelligence. According to data from OpenAlex, Salem A. Alyami has authored 92 papers receiving a total of 1.9k indexed citations (citations by other indexed papers that have themselves been cited), including 27 papers in Statistics and Probability, 16 papers in Statistics, Probability and Uncertainty and 15 papers in Artificial Intelligence. Recurrent topics in Salem A. Alyami's work include Statistical Distribution Estimation and Applications (26 papers), Probabilistic and Robust Engineering Design (15 papers) and Hydrology and Drought Analysis (8 papers). Salem A. Alyami is often cited by papers focused on Statistical Distribution Estimation and Applications (26 papers), Probabilistic and Robust Engineering Design (15 papers) and Hydrology and Drought Analysis (8 papers). Salem A. Alyami collaborates with scholars based in Saudi Arabia, Bangladesh and Australia. Salem A. Alyami's co-authors include Mohammad Ali Moni, AKM Azad, Naif Alotaibi, Md. Rashed-Al-Mahfuz, Shahadat Uddin, Ibrahim Elbatal, Mohammed Elgarhy, Mohammad Abu Yousuf, Ehab M. Almetwally and Khondokar Fida Hasan and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Scientific Reports.

In The Last Decade

Salem A. Alyami

83 papers receiving 1.9k citations

Hit Papers

Deep CNN-LSTM With Self-Attention Model for Human Activit... 2022 2026 2023 2024 2022 2024 40 80 120
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Deep CNN-LSTM With Self-Attention Model for Human Activity Recognition Using Wearable Sensor
    2022 144 citations Salem A. Alyami, Hanan Akhdar et al. profile →
  2. Machine learning-based network intrusion detection for big and imbalanced data using oversampling, stacking feature embedding and feature extraction
    2024 94 citations Salem A. Alyami, Mohammad Ali Moni et al. profile →

Peers

Salem A. Alyami
Lukas Meier Switzerland
Hua Zhou United States
Ahmet Arslan Türkiye
Shang‐Ming Zhou United Kingdom
Finale Doshi‐Velez United States
Xiaohong Gao China
Katherine Heller United States
Tingting Zhu China
Pedro J. García-Laencina Spain
Sijia Liu United States
Lukas Meier Switzerland
Salem A. Alyami
Citations per year, relative to Salem A. Alyami Salem A. Alyami (= 1×) peers Lukas Meier

Countries citing papers authored by Salem A. Alyami

Since Specialization
Citations

This map shows the geographic impact of Salem A. Alyami's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Salem A. Alyami with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Salem A. Alyami more than expected).

Fields of papers citing papers by Salem A. Alyami

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Salem A. Alyami. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Salem A. Alyami. The network helps show where Salem A. Alyami may publish in the future.

Co-authorship network of co-authors of Salem A. Alyami

This figure shows the co-authorship network connecting the top 25 collaborators of Salem A. Alyami. A scholar is included among the top collaborators of Salem A. Alyami based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Salem A. Alyami. Salem A. Alyami is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Azad, AKM, et al.. (2024). An interpretable electrocardiogram-based model for predicting arrhythmia and ischemia in cardiovascular disease. Results in Engineering. 24. 103381–103381. 16 indexed citations
2.
Alawady, M. A., et al.. (2024). Bivariate power Lomax Sarmanov distribution: Statistical properties, Reliability measures, and Parameter estimation. Alexandria Engineering Journal. 113. 593–610. 3 indexed citations
3.
Naeem, Nafeesa, Md. Ali Hossain, Md Nur Alam, et al.. (2024). An Integrated Framework to Identify Prognostic Biomarkers and Novel Therapeutic Targets in Hepatocellular Carcinoma-Based Disabilities. Biology. 13(12). 966–966.
4.
Nobel, S. M. Nuruzzaman, S M Masfequier Rahman Swapno, Md Babul Islam, et al.. (2024). A Novel Mixed Convolution Transformer Model for the Fast and Accurate Diagnosis of Glioma Subtypes. SHILAP Revista de lepidopterología. 7(5). 15 indexed citations
5.
Islam, Md. Monirul, Mohammod Abul Kashem, Salem A. Alyami, & Mohammad Ali Moni. (2023). Monitoring water quality metrics of ponds with IoT sensors and machine learning to predict fish species survival. Microprocessors and Microsystems. 102. 104930–104930. 18 indexed citations
6.
Ahmed, Fee Faysal, Md. Shahedur Rahman, Md Rashid, et al.. (2023). Identification of genetic biomarkers, drug targets and agents for respiratory diseases utilising integrated bioinformatics approaches. Scientific Reports. 13(1). 19072–19072. 6 indexed citations
7.
8.
Uddin, Md. Jamal, Md. Martuza Ahamad, Sakifa Aktar, et al.. (2023). An Integrated Statistical and Clinically Applicable Machine Learning Framework for the Detection of Autism Spectrum Disorder. Computers. 12(5). 92–92. 22 indexed citations
9.
Uddin, Md. Jamal, Md. Martuza Ahamad, Md. Abul Ala Walid, et al.. (2023). A Comparison of Machine Learning Techniques for the Detection of Type-2 Diabetes Mellitus: Experiences from Bangladesh. Information. 14(7). 376–376. 24 indexed citations
10.
Alotaibi, Naif M., et al.. (2023). Modified-opportunistic inspection and the case of remote, groundwater well-heads. Reliability Engineering & System Safety. 237. 109389–109389. 4 indexed citations
11.
Barakat, H. M., et al.. (2022). Cumulative Residual Tsallis Entropy-Based Test of Uniformity and Some New Findings. Mathematics. 10(5). 771–771. 9 indexed citations
12.
Alotaibi, Naif, Ibrahim Elbatal, Ehab M. Almetwally, et al.. (2022). Truncated Cauchy Power Weibull-G Class of Distributions: Bayesian and Non-Bayesian Inference Modelling for COVID-19 and Carbon Fiber Data. Mathematics. 10(9). 1565–1565. 32 indexed citations
13.
Ahamad, Md. Martuza, Sakifa Aktar, Md. Jamal Uddin, et al.. (2022). Adverse Effects of COVID-19 Vaccination: Machine Learning and Statistical Approach to Identify and Classify Incidences of Morbidity and Postvaccination Reactogenicity. Healthcare. 11(1). 31–31. 22 indexed citations
14.
15.
Ahamad, Md. Martuza, Sakifa Aktar, Md. Jamal Uddin, et al.. (2022). Early-Stage Detection of Ovarian Cancer Based on Clinical Data Using Machine Learning Approaches. Journal of Personalized Medicine. 12(8). 1211–1211. 37 indexed citations
16.
17.
Barakat, H. M., et al.. (2021). Fractional Entropy-Based Test of Uniformity with Power Comparisons. Journal of Mathematics. 2021. 1–7. 8 indexed citations
18.
Akter, Tania, Mohammad Hanif Ali, Md. Imran Khan, et al.. (2021). Improved Transfer-Learning-Based Facial Recognition Framework to Detect Autistic Children at an Early Stage. Brain Sciences. 11(6). 734–734. 71 indexed citations
19.
Alyami, Salem A., et al.. (2021). Integrative Systems Biology Approaches to Identify Potential Biomarkers and Pathways of Cervical Cancer. Journal of Personalized Medicine. 11(5). 363–363. 12 indexed citations
20.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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