Daby Sow
Impact in
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- Artificial Intelligence in Healthcare
- Electronic Health Records Systems
- Health Informatics top 5%
Papers in
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- Machine Learning in Healthcare 14
- Data Stream Mining Techniques 7
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- Advanced Database Systems and Queries 4
- Co-authors
- Maria Ebling (12 shared papers)Jimeng Sun (6 shared papers)John Davis (9 shared papers)Jianying Hu (6 shared papers)Shahram Ebadollahi (5 shared papers)Marion Blount (9 shared papers)Guruduth Banavar (3 shared papers)Hui Lei (2 shared papers)
- Journals
- Journal of the Neurological Sciences (1 paper)ACM SIGMETRICS Performance Evaluation Review (1 paper)ACM Transactions on Information Systems (1 paper)IBM Journal of Research and Development (1 paper)IBM Systems Journal (1 paper)
- Partner nations
- United StatesCanadaIsrael
In The Last Decade
Daby Sow
54 papers receiving 646 citations
Peers
Comparison fields: 5 of 102
- Health Information Management 102
- Health Informatics 24
- Signal Processing 101
- Computer Vision and Pattern Recognition 191
- Information Systems and Management 55
Countries citing papers authored by Daby Sow
This map shows the geographic impact of Daby Sow'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 Daby Sow with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daby Sow more than expected).
Fields of papers citing papers by Daby Sow
This network shows the impact of papers produced by Daby Sow. 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 Daby Sow. The network helps show where Daby Sow may publish in the future.
Co-authors
The 25 scholars most cited alongside Daby Sow, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 58 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2010 | 92 | |
| 2 | 2002 | 88 | |
| 3 | 2014 | 54 | |
| 4 | Predicting Patient's Trajectory of Physiological Data using Temporal Trends in Similar Patients: A System for Near-Term Prognostics. | 2010 | 49 |
| 5 | 2014 | 30 | |
| 6 | 2010 | 27 | |
| 7 | 2010 | 26 | |
| 8 | 2022 | 21 | |
| 9 | 2022 | 20 | |
| 10 | 2007 | 19 | |
| 11 | 2001 | 19 | |
| 12 | 2003 | 19 | |
| 13 | 2001 | 18 | |
| 14 | 2005 | 15 | |
| 15 | 2014 | 13 | |
| 16 | 2010 | 12 | |
| 17 | 2010 | 11 | |
| 18 | 2015 | 9 | |
| 19 | 2023 | 9 | |
| 20 | 2010 | 8 |
About Daby Sow
Daby Sow is a scholar working on Artificial Intelligence, Computer Networks and Communications, Signal Processing, Computer Vision and Pattern Recognition and Surgery, having authored 58 papers that have together received 693 indexed citations. Recurring topics across this work include Machine Learning in Healthcare (14 papers), Time Series Analysis and Forecasting (12 papers), Healthcare Technology and Patient Monitoring (8 papers), Context-Aware Activity Recognition Systems (7 papers), Data Stream Mining Techniques (7 papers), Computability, Logic, AI Algorithms (5 papers), Data Quality and Management (4 papers) and Advanced Database Systems and Queries (4 papers). The work is most often cited by research in Health Information Management (102 citations), Health Informatics (24 citations), Signal Processing (101 citations), Computer Vision and Pattern Recognition (191 citations) and Information Systems and Management (55 citations). Daby Sow has collaborated with scholars based in United States, Canada and Israel. Frequent co-authors include Maria Ebling, Jimeng Sun, John Davis, Jianying Hu, Shahram Ebadollahi, Marion Blount, Guruduth Banavar, Hui Lei, Carolyn McGregor and Andrew James. Their work appears in journals such as Journal of the Neurological Sciences, ACM SIGMETRICS Performance Evaluation Review, ACM Transactions on Information Systems, IBM Journal of Research and Development and IBM Systems Journal.
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.