Patricia Kovatch

4.2k total citations
29 papers, 256 citations indexed

About

Patricia Kovatch is a scholar working on Artificial Intelligence, Computer Networks and Communications and Infectious Diseases. According to data from OpenAlex, Patricia Kovatch has authored 29 papers receiving a total of 256 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Artificial Intelligence, 6 papers in Computer Networks and Communications and 5 papers in Infectious Diseases. Recurrent topics in Patricia Kovatch's work include Machine Learning in Healthcare (8 papers), Distributed and Parallel Computing Systems (6 papers) and COVID-19 Clinical Research Studies (5 papers). Patricia Kovatch is often cited by papers focused on Machine Learning in Healthcare (8 papers), Distributed and Parallel Computing Systems (6 papers) and COVID-19 Clinical Research Studies (5 papers). Patricia Kovatch collaborates with scholars based in United States, Switzerland and Italy. Patricia Kovatch's co-authors include Li Li, Nicholas P. Tatonetti, Andrew Kasarskis, Kipp W. Johnson, Joel T. Dudley, Khader Shameer, Alexandre Yahi, Phil Andrews, Partho P. Sengupta and Bruce Darrow and has published in prestigious journals such as Nature Communications, Annals of Internal Medicine and Scientific Reports.

In The Last Decade

Patricia Kovatch

26 papers receiving 248 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Patricia Kovatch United States 8 82 69 62 41 32 29 256
İbrahi̇m Karabayir United States 10 63 0.8× 121 1.8× 39 0.6× 29 0.7× 23 0.7× 28 377
Jumpei Sato Japan 7 98 1.2× 93 1.3× 76 1.2× 33 0.8× 75 2.3× 24 292
Borim Ryu South Korea 11 90 1.1× 23 0.3× 95 1.5× 19 0.5× 47 1.5× 27 323
Md. Martuza Ahamad Bangladesh 10 147 1.8× 42 0.6× 86 1.4× 27 0.7× 30 0.9× 18 396
Hsiu-An Lee Taiwan 12 38 0.5× 48 0.7× 27 0.4× 13 0.3× 33 1.0× 35 385
Gina Barnes United States 13 129 1.6× 44 0.6× 51 0.8× 78 1.9× 104 3.3× 31 486
Konstantinos Mitsis Greece 7 70 0.9× 24 0.3× 73 1.2× 15 0.4× 14 0.4× 11 275
Mohammad Adibuzzaman United States 8 46 0.6× 50 0.7× 39 0.6× 21 0.5× 26 0.8× 26 272
Xingzhi Sun China 8 85 1.0× 84 1.2× 24 0.4× 37 0.9× 39 1.2× 17 315
Minjie Xia China 7 123 1.5× 83 1.2× 84 1.4× 57 1.4× 79 2.5× 9 392

Countries citing papers authored by Patricia Kovatch

Since Specialization
Citations

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

Fields of papers citing papers by Patricia Kovatch

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Patricia Kovatch

This figure shows the co-authorship network connecting the top 25 collaborators of Patricia Kovatch. A scholar is included among the top collaborators of Patricia Kovatch 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 Patricia Kovatch. Patricia Kovatch 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.
Argulian, Edgar, Stamatios Lerakis, Pranai Tandon, et al.. (2026). Automated diagnosis of chronic obstructive pulmonary disease using deep learning applied to electrocardiograms. EBioMedicine. 123. 106066–106066.
2.
Holmes, Emma, Akhil Vaid, Alexander W. Charney, et al.. (2025). InfEHR: Clinical phenotype resolution through deep geometric learning on electronic health records. Nature Communications. 16(1). 8475–8475.
3.
Jiang, Joy, Patricia Kovatch, Mayte Suárez‐Fariñas, et al.. (2025). A foundational transformer leveraging full night, multichannel sleep study data accurately classifies sleep stages. SLEEP. 48(8). 2 indexed citations
4.
Soffer, Shelly, Mahmud Omar, Benjamin S. Glicksberg, et al.. (2025). A scalable framework for benchmark embedding models in semantic health-care tasks. Journal of the American Medical Informatics Association. 32(12). 1877–1887.
5.
Nadkarni, Girish N., Ankit Sakhuja, Eyal Klang, et al.. (2025). Summarize-then-Prompt: A Novel Prompt Engineering Strategy for Generating High-Quality Discharge Summaries. Applied Clinical Informatics. 16(4). 1325–1331. 1 indexed citations
6.
Jayaraman, Pushkala, Brian Y. Soong, Alexandra S. Reynolds, et al.. (2024). Derivation, external and clinical validation of a deep learning approach for detecting intracranial hypertension. npj Digital Medicine. 7(1). 233–233. 5 indexed citations
7.
Vaid, Akhil, Mayte Suárez‐Fariñas, Sanjeev Kaul, et al.. (2023). Implications of the Use of Artificial Intelligence Predictive Models in Health Care Settings. Annals of Internal Medicine. 176(10). 1358–1369. 23 indexed citations
8.
Oh, Won-Suk, Pushkala Jayaraman, Pranai Tandon, et al.. (2023). A novel method leveraging time series data to improve subphenotyping and application in critically ill patients with COVID-19. Artificial Intelligence in Medicine. 148. 102750–102750. 1 indexed citations
9.
Kovatch, Patricia, et al.. (2022). Autoencoders for sample size estimation for fully connected neural network classifiers. npj Digital Medicine. 5(1). 180–180. 7 indexed citations
10.
Vaid, Akhil, Joy Jiang, Karandeep Singh, et al.. (2022). Automated Determination of Left Ventricular Function Using Electrocardiogram Data in Patients on Maintenance Hemodialysis. Clinical Journal of the American Society of Nephrology. 17(7). 1017–1025. 7 indexed citations
11.
Jun, Tomi, Divij Mathew, Sharon Nirenberg, et al.. (2022). Multiethnic Investigation of Risk and Immune Determinants of COVID-19 Outcomes. Frontiers in Cellular and Infection Microbiology. 12. 933190–933190. 1 indexed citations
12.
Valle, Diane M. Del, Edgar Gonzalez‐Kozlova, Brett Marinelli, et al.. (2022). Quantitative chest computed tomography combined with plasma cytokines predict outcomes in COVID-19 patients. Heliyon. 8(8). e10166–e10166. 1 indexed citations
13.
Jun, Tomi, Sharon Nirenberg, Elisabet Pujadas, et al.. (2021). Analysis of sex-specific risk factors and clinical outcomes in COVID-19. Communications Medicine. 1(1). 3–3. 23 indexed citations
14.
Jun, Tomi, et al.. (2021). Prediction of individual COVID-19 diagnosis using baseline demographics and lab data. Scientific Reports. 11(1). 13913–13913. 6 indexed citations
15.
Kovatch, Patricia, et al.. (2020). Optimizing High-Performance Computing Systems for Biomedical Workloads. PubMed. 2020. 183–192. 2 indexed citations
16.
Stingone, Jeanette A., et al.. (2019). The CHEAR Data Repository: Facilitating children’s environmental health and exposome research through data harmonization, pooling and accessibility. Environmental Epidemiology. 3(Supplement 1). 382–382. 2 indexed citations
17.
Shameer, Khader, M. Mercedes Pérez-Rodríguez, Li Li, et al.. (2018). Pharmacological risk factors associated with hospital readmission rates in a psychiatric cohort identified using prescriptome data mining. BMC Medical Informatics and Decision Making. 18(S3). 79–79. 11 indexed citations
18.
Shameer, Khader, Kipp W. Johnson, Alexandre Yahi, et al.. (2016). PREDICTIVE MODELING OF HOSPITAL READMISSION RATES USING ELECTRONIC MEDICAL RECORD-WIDE MACHINE LEARNING: A CASE-STUDY USING MOUNT SINAI HEART FAILURE COHORT. PubMed. 22. 276–287. 106 indexed citations
19.
Kovatch, Patricia, et al.. (2011). Scheduling diverse high performance computing systems with the goal of maximizing utilization. 1–6. 5 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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