Shadi Ghiasi

499 total citations
28 papers, 335 citations indexed

About

Shadi Ghiasi is a scholar working on Cardiology and Cardiovascular Medicine, Cognitive Neuroscience and Biomedical Engineering. According to data from OpenAlex, Shadi Ghiasi has authored 28 papers receiving a total of 335 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Cardiology and Cardiovascular Medicine, 15 papers in Cognitive Neuroscience and 10 papers in Biomedical Engineering. Recurrent topics in Shadi Ghiasi's work include EEG and Brain-Computer Interfaces (14 papers), Heart Rate Variability and Autonomic Control (11 papers) and ECG Monitoring and Analysis (10 papers). Shadi Ghiasi is often cited by papers focused on EEG and Brain-Computer Interfaces (14 papers), Heart Rate Variability and Autonomic Control (11 papers) and ECG Monitoring and Analysis (10 papers). Shadi Ghiasi collaborates with scholars based in Italy, Iran and United Kingdom. Shadi Ghiasi's co-authors include Alberto Greco, Gaetano Valenza, Ali Ghaffari, Enzo Pasquale Scilingo, Riccardo Barbieri, Claudio Gentili, Simone Messerotti Benvenuti, K. H. Kiyani, Louise Thwaites and Tingting Zhu and has published in prestigious journals such as Scientific Reports, IEEE Transactions on Biomedical Engineering and Sensors.

In The Last Decade

Shadi Ghiasi

25 papers receiving 324 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Shadi Ghiasi Italy 10 144 126 80 61 57 28 335
F. Bereksi Reguig Algeria 9 148 1.0× 115 0.9× 62 0.8× 70 1.1× 54 0.9× 31 299
I.Y. Kim South Korea 7 113 0.8× 150 1.2× 23 0.3× 59 1.0× 49 0.9× 13 316
S.I. Kim South Korea 7 119 0.8× 143 1.1× 24 0.3× 68 1.1× 48 0.8× 17 387
Shreyasi Datta India 11 189 1.3× 214 1.7× 33 0.4× 101 1.7× 62 1.1× 40 466
Annamalai Natarajan United States 9 129 0.9× 160 1.3× 46 0.6× 41 0.7× 37 0.6× 16 320
Fuze Tian China 11 57 0.4× 118 0.9× 39 0.5× 44 0.7× 79 1.4× 37 298
Andrea Němcová Czechia 10 292 2.0× 135 1.1× 31 0.4× 197 3.2× 52 0.9× 24 429
Jeen-Shing Wang Taiwan 7 181 1.3× 145 1.2× 25 0.3× 117 1.9× 75 1.3× 9 410
Muhammad Zubair South Korea 8 261 1.8× 185 1.5× 36 0.5× 146 2.4× 65 1.1× 25 435
Erdenebayar Urtnasan South Korea 12 155 1.1× 187 1.5× 63 0.8× 214 3.5× 105 1.8× 40 553

Countries citing papers authored by Shadi Ghiasi

Since Specialization
Citations

This map shows the geographic impact of Shadi Ghiasi'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 Shadi Ghiasi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shadi Ghiasi more than expected).

Fields of papers citing papers by Shadi Ghiasi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Shadi Ghiasi. 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 Shadi Ghiasi. The network helps show where Shadi Ghiasi may publish in the future.

Co-authorship network of co-authors of Shadi Ghiasi

This figure shows the co-authorship network connecting the top 25 collaborators of Shadi Ghiasi. A scholar is included among the top collaborators of Shadi Ghiasi 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 Shadi Ghiasi. Shadi Ghiasi 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.
Hu, Alice & Shadi Ghiasi. (2023). The Role of Morphology and Heart Rate Variability Features in Detecting Arrhythmias from Short ECGs. Journal of Student Research. 12(1).
2.
Ghiasi, Shadi, et al.. (2023). Utilising Machine Learning to Predict Myocardial Infarction by Electrocardiogram Derived Respiration. Journal of Student Research. 12(3).
3.
Ghiasi, Shadi, Tingting Zhu, Ping Lü, et al.. (2022). Sepsis Mortality Prediction Using Wearable Monitoring in Low–Middle Income Countries. Sensors. 22(10). 3866–3866. 14 indexed citations
4.
Lü, Ping, Shadi Ghiasi, Jannis Hagenah, et al.. (2022). Classification of Tetanus Severity in Intensive-Care Settings for Low-Income Countries Using Wearable Sensing. Sensors. 22(17). 6554–6554. 5 indexed citations
5.
Lü, Ping, Jannis Hagenah, Shadi Ghiasi, et al.. (2022). Improving Classification of Tetanus Severity for Patients in Low-Middle Income Countries Wearing ECG Sensors by Using a CNN-Transformer Network. IEEE Transactions on Biomedical Engineering. 70(4). 1340–1350. 18 indexed citations
6.
Ghiasi, Shadi, et al.. (2020). Increased functional connectivity within alpha and theta frequency bands in dysphoria: A resting-state EEG study. Journal of Affective Disorders. 281. 199–207. 37 indexed citations
7.
Nardelli, M., Sara Condino, Shadi Ghiasi, et al.. (2020). Recognizing AR-guided manual tasks through autonomic nervous system correlates: a preliminary study. CINECA IRIS Institutial research information system (University of Pisa). 63. 1–6. 4 indexed citations
8.
Ghiasi, Shadi, Alberto Greco, Riccardo Barbieri, Enzo Pasquale Scilingo, & Gaetano Valenza. (2020). Assessing Autonomic Function from Electrodermal Activity and Heart Rate Variability During Cold-Pressor Test and Emotional Challenge. Scientific Reports. 10(1). 5406–5406. 74 indexed citations
9.
Callara, Alejandro Luis, Sara Condino, Shadi Ghiasi, et al.. (2020). A preliminary quantitative EEG study on Augmented Reality Guidance of Manual Tasks. CINECA IRIS Institutial research information system (University of Pisa). 1–5. 12 indexed citations
10.
Callara, Alejandro Luis, Laura Sebastiani, Enrica L. Santarcangelo, et al.. (2020). A preliminary study on parasympathetic-sympathetic interaction through the analysis of heart rate variability and electrodermal activity. Florence Research (University of Florence). 21. 1–2. 1 indexed citations
11.
Catrambone, Vincenzo, Alberto Greco, M. Nardelli, et al.. (2018). A new Modelling Framework to Study Time-Varying Directional Brain-Heart Interactions: Preliminary Evaluations and Perspectives. PubMed. 3. 4611–4614. 4 indexed citations
12.
Patanè, Andrea, Shadi Ghiasi, Enzo Pasquale Scilingo, & Marta Kwiatkowska. (2018). Automated Recognition of Sleep Arousal Using Multimodal and Personalized Deep Ensembles of Neural Networks. Computing in cardiology. 45. 9 indexed citations
13.
Ghaffari, Ali, et al.. (2017). Detection of pathological heart sounds. Physiological Measurement. 38(8). 1616–1630. 52 indexed citations
14.
Ghiasi, Shadi, et al.. (2017). Atrial Fibrillation Detection Using Feature Based Algorithm and Deep Conventional Neural Network. Computing in cardiology. 44. 32 indexed citations
15.
Ghiasi, Shadi, et al.. (2017). Diagnosis of Sleep Apnea by Evaluating Points Distri?bution in Poincare Plot of RR Intervals. Computing in cardiology. 4 indexed citations
16.
Ghiasi, Shadi, et al.. (2017). Nonlinear Analysis of Heart Sounds for the Detection of Cardiac Disorders Using Recurrence Quantification Analysis. Computing in cardiology. 3 indexed citations
17.
18.
Ghiasi, Shadi, et al.. (2016). Cycle Selection and Neuro:Voting System for Classifying Heart Sound Recordings. Computing in cardiology. 12 indexed citations
19.
Ghiasi, Shadi, et al.. (2016). Applying Quality Index Criterion for Flexible Multi:Detection of Heartbeat Using Features of Multimodal Data. Computing in cardiology. 43. 3 indexed citations
20.
Jafari, Roozbeh, et al.. (2006). Adaptive Medical Feature Extraction for Resource Constrained Distributed Embedded Systems. 506–511. 2 indexed citations

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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