Muhammad Ghous

4 papers receiving 503 citations

Muhammad Ghous's Hit Papers

External Validation of a Widely Implemented Proprietary Sepsis Prediction Model in Hospitalized Patients 2021 · 501 citations
5010+1+3Years since publication100200300400500

Peers

Muhammad Ghous
Comparison fields: 5 of 87
  • Health Informatics 190
  • Family Practice 32
  • Health Information Management 54
  • Epidemiology 142
  • Artificial Intelligence 149
Replace Nathan Brajer with:
Nathan Brajer United States
Jeremy A. Balch United States
Davy van de Sande Netherlands
Supawadee Suppadungsuk Thailand
Jessica Schwartz United States
Fawad Qureshi United States
H.M. Giannini United States
Wee Han Ng United Kingdom
Jennifer C. Ginestra United States
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Muhammad Ghous relative to Nathan Brajer United States Nathan Brajer's profile →
Citations per field
00.5×1.5×1.9×
Nathan Brajer · 1×
Citations per year

Countries citing papers authored by Muhammad Ghous

Since Specialization
Citations

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

Fields of papers citing papers by Muhammad Ghous

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 24 scholars most cited alongside Muhammad Ghous, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Muhammad Ghous Line = papers co-authored together Muhammad Ghous links everyone, so they are left out of the graph.

All Works

8 of 8 papers shown
#Work
1
External Validation of a Widely Implemented Proprietary Sepsis Prediction Model in Hospitalized Patients
Hit paper breakdown →
2021501
2 202211
3 20244
4 20222
5 20250
6 20240
7 20250
8 20220

About Muhammad Ghous

Muhammad Ghous is a scholar working on Pulmonary and Respiratory Medicine, Critical Care and Intensive Care Medicine, Strategy and Management, Radiological and Ultrasound Technology and Clinical Psychology, having authored 8 papers that have together received 518 indexed citations. Recurring topics across this work include Lung Cancer Research Studies (1 paper), Cancer Genomics and Diagnostics (1 paper), Microbial Metabolites in Food Biotechnology (1 paper), Respiratory Support and Mechanisms (1 paper), Intensive Care Unit Cognitive Disorders (1 paper), Strategic Planning and Analysis (1 paper), Global Health Workforce Issues (1 paper) and Economic and Environmental Valuation (1 paper). The work is most often cited by research in Health Informatics (190 citations), Family Practice (32 citations), Health Information Management (54 citations), Epidemiology (142 citations) and Artificial Intelligence (149 citations). Muhammad Ghous has collaborated with scholars based in Pakistan, United States and Nigeria. Frequent co-authors include Erkin Ötleş, Andrew E. Krumm, John P. Donnelly, Jeffrey S. McCullough, M. Phillips, Karandeep Singh, Andrew Wong, Catherine L. Hough, Thomas S. Valley and Theodore J. Iwashyna. Their work appears in journals such as JAMA Internal Medicine, Critical Care Medicine, Innovation in Aging, Annals of the American Thoracic Society and Arabian Journal of Geosciences.

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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