Stan Kachnowski

1.1k total citations
23 papers, 791 citations indexed

About

Stan Kachnowski is a scholar working on General Health Professions, Public Health, Environmental and Occupational Health and Physiology. According to data from OpenAlex, Stan Kachnowski has authored 23 papers receiving a total of 791 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in General Health Professions, 4 papers in Public Health, Environmental and Occupational Health and 4 papers in Physiology. Recurrent topics in Stan Kachnowski's work include Mobile Health and mHealth Applications (6 papers), Artificial Intelligence in Healthcare and Education (3 papers) and Electronic Health Records Systems (3 papers). Stan Kachnowski is often cited by papers focused on Mobile Health and mHealth Applications (6 papers), Artificial Intelligence in Healthcare and Education (3 papers) and Electronic Health Records Systems (3 papers). Stan Kachnowski collaborates with scholars based in India, United States and Australia. Stan Kachnowski's co-authors include Tigest Tamrat, Ilene L. Hollin, Wei Jin, Paul Cuddihy, Mathew S. Maurer, Susan Delisle, Alex Trzebucki, Adel Ardalan, Hisham M. Abu‐Rayya and Candice Presseau and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal of the American Geriatrics Society and Journal of Medical Internet Research.

In The Last Decade

Stan Kachnowski

23 papers receiving 763 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Stan Kachnowski India 11 443 143 108 89 83 23 791
Louise Watson United Kingdom 4 598 1.3× 146 1.0× 120 1.1× 134 1.5× 47 0.6× 5 870
Lucien JLPG Engelen Netherlands 18 498 1.1× 71 0.5× 120 1.1× 81 0.9× 55 0.7× 26 1.4k
Brent I. Fox United States 15 335 0.8× 123 0.9× 119 1.1× 46 0.5× 136 1.6× 111 932
Santosh Krishna United States 9 953 2.2× 121 0.8× 174 1.6× 260 2.9× 89 1.1× 15 1.4k
Arunangsu Chatterjee United Kingdom 12 346 0.8× 62 0.4× 187 1.7× 95 1.1× 33 0.4× 38 739
Nikolaos Mastellos United Kingdom 17 394 0.9× 39 0.3× 177 1.6× 140 1.6× 86 1.0× 37 839
Tigest Tamrat Switzerland 14 563 1.3× 189 1.3× 149 1.4× 64 0.7× 45 0.5× 39 812
Ehsan Nabovati Iran 17 266 0.6× 42 0.3× 83 0.8× 76 0.9× 142 1.7× 61 675
Marcelo D’Agostino United States 8 615 1.4× 95 0.7× 186 1.7× 220 2.5× 33 0.4× 35 892
Maria Beatriz Moreira Alkmim Brazil 13 850 1.9× 137 1.0× 299 2.8× 235 2.6× 87 1.0× 36 1.3k

Countries citing papers authored by Stan Kachnowski

Since Specialization
Citations

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

Fields of papers citing papers by Stan Kachnowski

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Stan Kachnowski

This figure shows the co-authorship network connecting the top 25 collaborators of Stan Kachnowski. A scholar is included among the top collaborators of Stan Kachnowski 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 Stan Kachnowski. Stan Kachnowski 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.
Kachnowski, Stan, et al.. (2024). Assessing the Usability and Effectiveness of an AI-Powered Telehealth Platform: Mixed Methods Study on the Perspectives of Patients and Providers. JMIR Formative Research. 8. e62742–e62742. 1 indexed citations
2.
Kachnowski, Stan, et al.. (2023). Current and Potential Applications of Ambient Artificial Intelligence. SHILAP Revista de lepidopterología. 1(3). 241–246. 5 indexed citations
3.
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5.
Tang, Jian Jenny, et al.. (2022). Consumer acceptance of using a digital technology to manage postpartum depression. SHILAP Revista de lepidopterología. 3. 844172–844172. 3 indexed citations
6.
Hocking, Darren R., Adel Ardalan, Hisham M. Abu‐Rayya, et al.. (2022). Feasibility of a virtual reality-based exercise intervention and low-cost motion tracking method for estimation of motor proficiency in youth with autism spectrum disorder. Journal of NeuroEngineering and Rehabilitation. 19(1). 1–1. 44 indexed citations
7.
Kachnowski, Stan, et al.. (2019). Patient Perspective of Blockchain Technology in Clinical Trial Management: A Proof of Concept Study (Preprint). Journal of Medical Internet Research. 1 indexed citations
8.
Kachnowski, Stan, et al.. (2016). The Impact of Wearable Device Enabled Health Initiative on Physical Activity and Sleep. Cureus. 8(10). e825–e825. 19 indexed citations
9.
Kachnowski, Stan, et al.. (2013). Do Patients “Like” Good Care? Measuring Hospital Quality via Facebook. American Journal of Medical Quality. 28(5). 374–382. 53 indexed citations
10.
Tamrat, Tigest, et al.. (2012). “Think Different”: A Qualitative Assessment of Commercial Innovation for Diabetes Information Technology Programs. Diabetes Technology & Therapeutics. 14(11). 1023–1029. 1 indexed citations
11.
Hollin, Ilene L., Margaret L. Griffin, & Stan Kachnowski. (2012). How will we know if it’s working? A multi-faceted approach to measuring usability of a specialty-specific electronic medical record. Health Informatics Journal. 18(3). 219–232. 10 indexed citations
12.
Griffin, Margaret L., et al.. (2012). Innovation Spaces. The Health Care Manager. 31(2). 166–177. 4 indexed citations
13.
Griffin, Margaret, et al.. (2012). Falling short: Recruiting elderly individuals for a fall study. Ageing Research Reviews. 12(2). 552–560. 12 indexed citations
14.
Tamrat, Tigest & Stan Kachnowski. (2011). Special Delivery: An Analysis of mHealth in Maternal and Newborn Health Programs and Their Outcomes Around the World. Maternal and Child Health Journal. 16(5). 1092–1101. 242 indexed citations
15.
Jin, Wei, Ilene L. Hollin, & Stan Kachnowski. (2011). A review of the use of mobile phone text messaging in clinical and healthy behaviour interventions. Journal of Telemedicine and Telecare. 17(1). 41–48. 204 indexed citations
16.
Kakade, Anagha, Qian Gao, Paul Cuddihy, et al.. (2010). Maximum Daily 6 Minutes of Activity: An Index of Functional Capacity Derived from Actigraphy and Its Application to Older Adults with Heart Failure. Journal of the American Geriatrics Society. 58(5). 931–936. 32 indexed citations
17.
Trzebucki, Alex, et al.. (2009). Synchronous communication facilitates interruptive workflow for attending physicians and nurses in clinical settings. International Journal of Medical Informatics. 78(9). 629–637. 56 indexed citations
18.
Delisle, Susan, et al.. (2008). Actigraphy in Heart Failure Subjects with a Reduced and Normal Ejection Fraction. Journal of Cardiac Failure. 14(6). S110–S110. 3 indexed citations
19.
Maurer, Mathew S., et al.. (2008). The Prevalence and Impact of Anergia (Lack of Energy) in Subjects With Heart Failure and its Associations With Actigraphy. Journal of Cardiac Failure. 15(2). 145–151. 23 indexed citations
20.
Melnikas, Andrea, et al.. (2008). Understanding communication capacity. Communication patterns and ICT usage in clinical settings.. PubMed. 22(3). 34–41. 9 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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