Sehj Kashyap

538 total citations
10 papers, 311 citations indexed

About

Sehj Kashyap is a scholar working on Health Information Management, Artificial Intelligence and Pediatrics, Perinatology and Child Health. According to data from OpenAlex, Sehj Kashyap has authored 10 papers receiving a total of 311 indexed citations (citations by other indexed papers that have themselves been cited), including 3 papers in Health Information Management, 3 papers in Artificial Intelligence and 2 papers in Pediatrics, Perinatology and Child Health. Recurrent topics in Sehj Kashyap's work include Machine Learning in Healthcare (3 papers), Artificial Intelligence in Healthcare (2 papers) and Child Nutrition and Water Access (2 papers). Sehj Kashyap is often cited by papers focused on Machine Learning in Healthcare (3 papers), Artificial Intelligence in Healthcare (2 papers) and Child Nutrition and Water Access (2 papers). Sehj Kashyap collaborates with scholars based in United States, India and Netherlands. Sehj Kashyap's co-authors include Mark Sendak, Kristin Corey, Suresh Balu, Mitchell T. Heflin, Madhav Swaminathan, Elizabeth Lorenzi, Sandhya Lagoo‐Deenadayalan, Shelley R. McDonald, Katherine Heller and Michael Gao and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS Medicine and Journal of the American Medical Informatics Association.

In The Last Decade

Sehj Kashyap

9 papers receiving 302 citations

Peers

Countries citing papers authored by Sehj Kashyap

Since Specialization

Citations

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

Fields of papers citing papers by Sehj Kashyap

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sehj Kashyap

This figure shows the co-authorship network connecting the top 25 collaborators of Sehj Kashyap. A scholar is included among the top collaborators of Sehj Kashyap 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 Sehj Kashyap. Sehj Kashyap is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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10 of 10 papers shown

#	Work	Indexed citations
1	Drug Standardization, HPTLC fingerprinting, toxicological research studies of ASU herbal drug fruit seeds part of Peucedanum grande C.B. Clarke 2024 ·International Journal of Herbal Medicine ·(unknown), Md Wadud Ahmed, Sehj Kashyap, (unknown), (unknown)	1
2	Impact of family-centred postnatal training on maternal and neonatal health and care practices in district hospitals in two states in India: a pre–post study 2022 ·BMJ Open Quality ·Sehj Kashyap, (unknown), (unknown), (unknown), Rashmi Pant, Baljit Kaur, (unknown), R. Premkumar, (unknown), Bhanu Pratap, Anand Kumar, (unknown), (unknown)	4
3	Impact of diagnosis code grouping method on clinical prediction model performance: A multi-site retrospective observational study 2021 ·International Journal of Medical Informatics ·Aman Kansal, Michael Gao, Suresh Balu, Marshall Nichols, Kristin Corey, Sehj Kashyap, Mark Sendak	4
4	A survey of extant organizational and computational setups for deploying predictive models in health systems 2021 ·Journal of the American Medical Informatics Association ·Sehj Kashyap, Keith Morse, Birju Patel, Nigam H. Shah	17
5	A framework for making predictive models useful in practice 2020 ·Journal of the American Medical Informatics Association ·Kenneth Jung, Sehj Kashyap, Anand Avati, Stephanie Harman, Heather Shaw, Ron Li, Margaret Smith, (unknown), (unknown), (unknown), Tina Seto, Steven C. Bagley, Nigam H. Shah	44
6	Measure what matters: Counts of hospitalized patients are a better metric for health system capacity planning for a reopening 2020 ·Journal of the American Medical Informatics Association ·Sehj Kashyap, Saurabh Gombar, Steve Yadlowsky, Alison Callahan, Jason Fries, Benjamin A. Pinsky, Nigam H. Shah	11
7	Just-in-time postnatal education programmes to improve newborn care practices: needs and opportunities in low-resource settings 2020 ·BMJ Global Health ·(unknown), (unknown), (unknown), (unknown), Megan Marx Delaney, (unknown), (unknown), (unknown), (unknown), Sehj Kashyap, (unknown), (unknown), Griffith Bell, Baljit Kaur, (unknown), Archana Mishra, (unknown), Katherine Semrau	13
8	A Path for Translation of Machine Learning Products into Healthcare Delivery 2020 ·SHILAP Revista de lepidopterología ·Mark Sendak, (unknown), Sehj Kashyap, Michael Gao, Marshall Nichols, Kristin Corey, William Ratliff, Suresh Balu	78
9	Development and validation of machine learning models to identify high-risk surgical patients using automatically curated electronic health record data (Pythia): A retrospective, single-site study 2018 ·PLoS Medicine ·Kristin Corey, Sehj Kashyap, Elizabeth Lorenzi, Sandhya Lagoo‐Deenadayalan, Katherine Heller, (unknown), Suresh Balu, Mitchell T. Heflin, Shelley R. McDonald, Madhav Swaminathan, Mark Sendak	138
10	Cocaine use a risk factor for DKA 2004 ·(unknown), Krishnan Anand, Sehj Kashyap	1

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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