Asma Ghandeharioun

1.6k total citations
20 papers, 854 citations indexed

About

Asma Ghandeharioun is a scholar working on Health Information Management, Artificial Intelligence and Experimental and Cognitive Psychology. According to data from OpenAlex, Asma Ghandeharioun has authored 20 papers receiving a total of 854 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Health Information Management, 8 papers in Artificial Intelligence and 6 papers in Experimental and Cognitive Psychology. Recurrent topics in Asma Ghandeharioun's work include Artificial Intelligence in Healthcare (8 papers), Imbalanced Data Classification Techniques (4 papers) and Digital Mental Health Interventions (4 papers). Asma Ghandeharioun is often cited by papers focused on Artificial Intelligence in Healthcare (8 papers), Imbalanced Data Classification Techniques (4 papers) and Digital Mental Health Interventions (4 papers). Asma Ghandeharioun collaborates with scholars based in United States, Iran and United Kingdom. Asma Ghandeharioun's co-authors include Rosalind W. Picard, Roohallah Alizadehsani, Reihane Boghrati, Zahra Alizadeh Sani, Mohammad Javad Hosseini, Hoda Mashayekhi, Behdad Bahadorian, Jafar Habibi, Asaph Azaria and Sara Taylor and has published in prestigious journals such as Computer Methods and Programs in Biomedicine, Frontiers in Psychiatry and Journal of Medical Signals & Sensors.

In The Last Decade

Asma Ghandeharioun

20 papers receiving 807 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Asma Ghandeharioun United States 14 363 302 211 177 142 20 854
Shruti Garg India 11 236 0.7× 287 1.0× 136 0.6× 37 0.2× 77 0.5× 29 690
Neha Prerna Tigga India 4 200 0.6× 202 0.7× 130 0.6× 40 0.2× 81 0.6× 8 497
Franco Chiarugi Greece 17 116 0.3× 111 0.4× 184 0.9× 380 2.1× 38 0.3× 66 1.1k
Ane Alberdi Spain 10 59 0.2× 244 0.8× 193 0.9× 151 0.9× 41 0.3× 17 926
Stanisław Saganowski Poland 11 45 0.1× 161 0.5× 201 1.0× 62 0.4× 32 0.2× 28 573
Enrique Garcia-Ceja Norway 13 32 0.1× 252 0.8× 257 1.2× 43 0.2× 179 1.3× 27 991
Faisal Farooq United States 14 65 0.2× 223 0.7× 40 0.2× 77 0.4× 37 0.3× 45 753
Susel Góngora Alonso Spain 11 52 0.1× 124 0.4× 45 0.2× 25 0.1× 67 0.5× 18 564
Scott L. Fleming United States 13 80 0.2× 251 0.8× 82 0.4× 27 0.2× 22 0.2× 27 734
Ravinder Ahuja India 12 42 0.1× 246 0.8× 70 0.3× 35 0.2× 18 0.1× 22 536

Countries citing papers authored by Asma Ghandeharioun

Since Specialization
Citations

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

Fields of papers citing papers by Asma Ghandeharioun

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Asma Ghandeharioun

This figure shows the co-authorship network connecting the top 25 collaborators of Asma Ghandeharioun. A scholar is included among the top collaborators of Asma Ghandeharioun 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 Asma Ghandeharioun. Asma Ghandeharioun 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.
Pedrelli, Paola, Szymon Fedor, Asma Ghandeharioun, et al.. (2020). Monitoring Changes in Depression Severity Using Wearable and Mobile Sensors. Frontiers in Psychiatry. 11. 584711–584711. 83 indexed citations
2.
3.
Picard, Rosalind W. & Asma Ghandeharioun. (2019). Characterizing Sources of Uncertainty to Proxy Calibration and Disambiguate Annotator and Data Bias. DSpace@MIT (Massachusetts Institute of Technology). 8 indexed citations
4.
Ghandeharioun, Asma, Judy Hanwen Shen, Natasha Jaques, et al.. (2019). Approximating Interactive Human Evaluation with Self-Play for Open-Domain Dialog Systems. DSpace@MIT (Massachusetts Institute of Technology). 32. 13658–13669. 10 indexed citations
5.
Jaques, Natasha, et al.. (2019). Analysis of Online Suicide Risk with Document Embeddings and Latent Dirichlet Allocation. 1–5. 8 indexed citations
6.
Jaques, Natasha, Asma Ghandeharioun, Judy Hanwen Shen, et al.. (2019). Way Off-Policy Batch Deep Reinforcement Learning of Human Preferences in Dialog. 1 indexed citations
7.
Saeedi, Ardavan, Matthew D. Hoffman, Stephen DiVerdi, et al.. (2018). Multimodal Prediction and Personalization of Photo Edits with Deep Generative Models. International Conference on Artificial Intelligence and Statistics. 1309–1317. 2 indexed citations
8.
Ghandeharioun, Asma & Rosalind W. Picard. (2017). BrightBeat. 1624–1631. 54 indexed citations
9.
Ghandeharioun, Asma, Szymon Fedor, Dawn F. Ionescu, et al.. (2017). Objective assessment of depressive symptoms with machine learning and wearable sensors data. 325–332. 72 indexed citations
10.
Pedrelli, Paola, Esther Howe, David Mischoulon, et al.. (2017). Integrating Ema, Clinical Assessment and Wearable Sensors to Examine the Association between Major DepressiveDisorder (MDD) and Alcohol Use. Iproceedings. 3(1). e51–e51. 1 indexed citations
11.
Ghandeharioun, Asma, Asaph Azaria, Sara Taylor, & Rosalind W. Picard. (2016). “Kind and Grateful”: A Context-Sensitive Smartphone App Utilizing Inspirational Content to Promote Gratitude. PubMed. 6(1). 9–9. 31 indexed citations
12.
Jaques, Natasha, Sara Taylor, Asaph Azaria, et al.. (2015). Predicting students' happiness from physiology, phone, mobility, and behavioral data. PubMed. 2015. 222–228. 85 indexed citations
13.
Alizadehsani, Roohallah, Jafar Habibi, Mohammad Javad Hosseini, et al.. (2013). A data mining approach for diagnosis of coronary artery disease. Computer Methods and Programs in Biomedicine. 111(1). 52–61. 215 indexed citations
14.
Alizadehsani, Roohallah, Jafar Habibi, Hoda Mashayekhi, et al.. (2013). Diagnosing coronary artery disease via data mining algorithms by considering laboratory and echocardiography features. Research in Cardiovascular Medicine. 2(3). 133–133. 52 indexed citations
15.
Alizadehsani, Roohallah, Jafar Habibi, Mohammad Javad Hosseini, et al.. (2012). Diagnosis of coronary artery disease using data mining techniques based on symptoms and ECG features. Own your potential (DEAKIN). 82(4). 542–553. 42 indexed citations
16.
Alizadehsani, Roohallah, Mohammad Javad Hosseini, Zahra Alizadeh Sani, Asma Ghandeharioun, & Reihane Boghrati. (2012). Diagnosis of Coronary Artery Disease Using Cost-Sensitive Algorithms. 9–16. 63 indexed citations
17.
Alizadehsani, Roohallah, Jafar Habibi, Behdad Bahadorian, et al.. (2012). Diagnosis of coronary arteries stenosis using data mining. Journal of Medical Signals & Sensors. 2(3). 153–153. 22 indexed citations
18.
Alizadehsani, Roohallah, Mohammad Javad Hosseini, Reihane Boghrati, et al.. (2012). Exerting Cost-Sensitive and Feature Creation Algorithms for Coronary Artery Disease Diagnosis. RePEc: Research Papers in Economics. 3(1). 59–79. 38 indexed citations
19.
Alizadehsani, Roohallah, Jafar Habibi, Behdad Bahadorian, et al.. (2012). Diagnosis of coronary arteries stenosis using data mining.. PubMed. 2(3). 153–9. 21 indexed citations
20.
Alizadehsani, Roohallah, Jafar Habibi, Roohallah Alizadehsani, et al.. (2012). Diagnosis of Coronary Artery Disease Using Data Mining Based on Lab Data and Echo Features. 1(1). 26–29. 28 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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