Matthew M. Ruppert

1.4k total citations
42 papers, 696 citations indexed

About

Matthew M. Ruppert is a scholar working on Cardiology and Cardiovascular Medicine, Critical Care and Intensive Care Medicine and Artificial Intelligence. According to data from OpenAlex, Matthew M. Ruppert has authored 42 papers receiving a total of 696 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Cardiology and Cardiovascular Medicine, 13 papers in Critical Care and Intensive Care Medicine and 10 papers in Artificial Intelligence. Recurrent topics in Matthew M. Ruppert's work include Cardiac, Anesthesia and Surgical Outcomes (13 papers), Intensive Care Unit Cognitive Disorders (11 papers) and Machine Learning in Healthcare (9 papers). Matthew M. Ruppert is often cited by papers focused on Cardiac, Anesthesia and Surgical Outcomes (13 papers), Intensive Care Unit Cognitive Disorders (11 papers) and Machine Learning in Healthcare (9 papers). Matthew M. Ruppert collaborates with scholars based in United States, Australia and Germany. Matthew M. Ruppert's co-authors include Azra Bihorac, Tezcan Ozrazgat‐Baslanti, Parisa Rashidi, Benjamin Shickel, Tyler J. Loftus, Gilbert R. Upchurch, Patrick Tighe, Feng Zheng, Haleh Hashemighouchani and Yuanfang Ren and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Annals of Surgery.

In The Last Decade

Matthew M. Ruppert

39 papers receiving 676 citations

Peers

Countries citing papers authored by Matthew M. Ruppert

Since Specialization

Citations

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

Fields of papers citing papers by Matthew M. Ruppert

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Matthew M. Ruppert. 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 Matthew M. Ruppert. The network helps show where Matthew M. Ruppert may publish in the future.

Co-authorship network of co-authors of Matthew M. Ruppert

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

All Works

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20 of 20 papers shown

#	Work	Indexed citations
1	Electronic Health Record Data Quality and Performance Assessments: Scoping Review 2024 ·JMIR Medical Informatics ·(unknown), (unknown), Matthew M. Ruppert, (unknown), (unknown), (unknown), Jeremy A. Balch, Tezcan Ozrazgat‐Baslanti, Benjamin Shickel, Tyler J. Loftus, Azra Bihorac	1
2	Community-engaged artificial intelligence research: A scoping review 2024 ·SHILAP Revista de lepidopterología ·Tyler J. Loftus, Jeremy A. Balch, Kenneth L. Abbott, (unknown), Matthew M. Ruppert, Benjamin Shickel, Tezcan Ozrazgat‐Baslanti, Philip A. Efron, Patrick Tighe, William R. Hogan, Parisa Rashidi, Michelle I. Cardel, Gilbert R. Upchurch, Azra Bihorac	8
3	Association of Sociodemographic Factors With Overtriage, Undertriage, and Value of Care After Major Surgery 2024 ·SHILAP Revista de lepidopterología ·Tyler J. Loftus, Matthew M. Ruppert, Benjamin Shickel, Tezcan Ozrazgat‐Baslanti, Jeremy A. Balch, Kenneth L. Abbott, (unknown), (unknown), Firas Madbak, Faheem W. Guirgis, David Skarupa, Philip A. Efron, Patrick Tighe, William R. Hogan, Parisa Rashidi, Gilbert R. Upchurch, Azra Bihorac	0
4	Identifying acute illness phenotypes via deep temporal interpolation and clustering network on physiologic signatures 2024 ·Scientific Reports ·Yuanfang Ren, Yanjun Li, Tyler J. Loftus, Jeremy A. Balch, Kenneth L. Abbott, Matthew M. Ruppert, (unknown), Benjamin Shickel, Parisa Rashidi, Tezcan Ozrazgat‐Baslanti, Azra Bihorac	1
5	Machine Learning–Enabled Clinical Information Systems Using Fast Healthcare Interoperability Resources Data Standards: Scoping Review 2023 ·JMIR Medical Informatics ·Jeremy A. Balch, Matthew M. Ruppert, Tyler J. Loftus, (unknown), Yuanfang Ren, Gilbert R. Upchurch, Tezcan Ozrazgat‐Baslanti, Parisa Rashidi, Azra Bihorac	21
6	Machine learning-enabled clinical information systems using fast healthcare interoperability data standards: a scoping review (Preprint) 2023 ·Jeremy A. Balch, Matthew M. Ruppert, Tyler J. Loftus, (unknown), Yuanfang Ren, Gilbert R. Upchurch, Tezcan Ozrazgat‐Baslanti, Parisa Rashidi, Azra Bihorac	0
7	Dynamic predictions of postoperative complications from explainable, uncertainty-aware, and multi-task deep neural networks 2023 ·Scientific Reports ·Benjamin Shickel, Tyler J. Loftus, Matthew M. Ruppert, Gilbert R. Upchurch, Tezcan Ozrazgat‐Baslanti, Parisa Rashidi, Azra Bihorac	23
8	Building an automated, machine learning-enabled platform for predicting post-operative complications 2023 ·Physiological Measurement ·Jeremy A. Balch, Matthew M. Ruppert, Benjamin Shickel, Tezcan Ozrazgat‐Baslanti, Patrick Tighe, Philip A. Efron, Gilbert R. Upchurch, Parisa Rashidi, Azra Bihorac, Tyler J. Loftus	4
9	The effect of non-pharmacologic strategies on prevention or management of intensive care unit delirium: a systematic review 2022 ·F1000Research ·(unknown), Haleh Hashemighouchani, (unknown), Matthew M. Ruppert, (unknown), Tezcan Ozrazgat‐Baslanti, Parisa Rashidi, Azra Bihorac	0
10	Ideal algorithms in healthcare: Explainable, dynamic, precise, autonomous, fair, and reproducible 2022 ·SHILAP Revista de lepidopterología ·Tyler J. Loftus, Patrick Tighe, Tezcan Ozrazgat‐Baslanti, John P. Davis, Matthew M. Ruppert, Yuanfang Ren, Benjamin Shickel, Rishikesan Kamaleswaran, William R. Hogan, J. Randall Moorman, Gilbert R. Upchurch, Parisa Rashidi, Azra Bihorac	31
11	Physiologic signatures within six hours of hospitalization identify acute illness phenotypes 2022 ·SHILAP Revista de lepidopterología ·Yuanfang Ren, Tyler J. Loftus, Yanjun Li, (unknown), Matthew M. Ruppert, Shounak Datta, Gilbert R. Upchurch, Patrick Tighe, Parisa Rashidi, Benjamin Shickel, Tezcan Ozrazgat‐Baslanti, Azra Bihorac	2
12	Uncertainty-aware deep learning in healthcare: A scoping review 2022 ·SHILAP Revista de lepidopterología ·Tyler J. Loftus, Benjamin Shickel, Matthew M. Ruppert, Jeremy A. Balch, Tezcan Ozrazgat‐Baslanti, Patrick Tighe, Philip A. Efron, William R. Hogan, Parisa Rashidi, Gilbert R. Upchurch, Azra Bihorac	28
13	Federated learning for preserving data privacy in collaborative healthcare research 2022 ·Digital Health ·Tyler J. Loftus, Matthew M. Ruppert, Benjamin Shickel, Tezcan Ozrazgat‐Baslanti, Jeremy A. Balch, Philip A. Efron, Gilbert R. Upchurch, Parisa Rashidi, Christopher J. Tignanelli, Jiang Bian, Azra Bihorac	32
14	The effect of non-pharmacologic strategies on prevention or management of intensive care unit delirium: a systematic review 2021 ·F1000Research ·(unknown), Haleh Hashemighouchani, (unknown), Matthew M. Ruppert, (unknown), Tezcan Ozrazgat‐Baslanti, Parisa Rashidi, Azra Bihorac	6
15	Deep Multi-Modal Transfer Learning for Augmented Patient Acuity Assessment in the Intelligent ICU 2021 ·Frontiers in Digital Health ·Benjamin Shickel, Anis Davoudi, Tezcan Ozrazgat‐Baslanti, Matthew M. Ruppert, Azra Bihorac, Parisa Rashidi	14
16	The impact of environmental risk factors on delirium and benefits of noise and light modifications: a scoping review 2020 ·F1000Research ·Haleh Hashemighouchani, (unknown), (unknown), Matthew M. Ruppert, (unknown), Tezcan Ozrazgat‐Baslanti, Parisa Rashidi, Azra Bihorac	4
17	The effect of non-pharmacologic strategies on prevention or management of intensive care unit delirium: a systematic review 2020 ·F1000Research ·(unknown), Haleh Hashemighouchani, (unknown), Matthew M. Ruppert, (unknown), Tezcan Ozrazgat‐Baslanti, Parisa Rashidi, Azra Bihorac	6
18	Added Value of Intraoperative Data for Predicting Postoperative Complications: The MySurgeryRisk PostOp Extension 2020 ·Journal of Surgical Research ·Shounak Datta, Tyler J. Loftus, Matthew M. Ruppert, Chris Giordano, Gilbert R. Upchurch, Parisa Rashidi, Tezcan Ozrazgat‐Baslanti, Azra Bihorac	25
19	Improved predictive models for acute kidney injury with IDEA: Intraoperative Data Embedded Analytics 2019 ·PLoS ONE ·Lasith Adhikari, Tezcan Ozrazgat‐Baslanti, Matthew M. Ruppert, R. W. M. A. Madushani, (unknown), Haleh Hashemighouchani, Feng Zheng, Ming Tao, (unknown), Xiaolin Li, Parisa Rashidi, Azra Bihorac	58
20	Intelligent ICU for Autonomous Patient Monitoring Using Pervasive Sensing and Deep Learning 2019 ·Scientific Reports ·Anis Davoudi, (unknown), Benjamin Shickel, Scott Siegel, (unknown), Matthew M. Ruppert, (unknown), Tezcan Ozrazgat‐Baslanti, Patrick Tighe, Azra Bihorac, Parisa Rashidi	92

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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