Matthew Sperrin

11.0k citations
161 papers · 4.4k indexed · 3 hit papers · h-index 37

Impact in

Papers in

Matthew Sperrin

155 papers receiving 4.3k citations

Hit Papers

Evaluation of clinical prediction models (part 1): from development to external validation 2024 · 183 citations
1832016202620192022100200300400

Peers

Matthew Sperrin
Comparison fields: 5 of 183
  • Health Informatics 117
  • Cardiology and Cardiovascular Medicine 1.1k
  • Health Information Management 193
  • Geriatrics and Gerontology 156
  • Statistics and Probability 243
Replace Nirav R. Shah with:
Nirav R. Shah United States
Joie Ensor United Kingdom
Kym I E Snell United Kingdom
Glen P. Martin United Kingdom
Thomas P. A. Debray Netherlands
Darío Gregori Italy
Benjamin A. Goldstein United States
Spiros Denaxas United Kingdom
Harriette G.C. Van Spall Canada
Nicole Pratt Australia
Matthew Sperrin relative to Nirav R. Shah United States Nirav R. Shah's profile →
Citations per field
00.5×1.5×2.3×
Nirav R. Shah · 1×
Citations per year

Countries citing papers authored by Matthew Sperrin

Since Specialization
Citations

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

Fields of papers citing papers by Matthew Sperrin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 25 scholars most cited alongside Matthew Sperrin, 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 Matthew Sperrin Line = papers co-authored together Matthew Sperrin links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20255
2 20240
3 20242
4 20241
5 20242
6 20241
7 20233
8 20232
9 20235
10 202112
11 20218
12 202080
13
Informative Observation in Health Data: Association of Past Level and Trend with Time to Next Measurement.
20177
14
Can we identify people with higher pancreatic cancer risk who present with type 2 diabetes
20172
15 201750
16 201715
17 201615
18 201628
19 20153
20 201533

About Matthew Sperrin

Matthew Sperrin is a scholar working on Statistics and Probability, Applied Microbiology and Biotechnology, Health Information Management, Geriatrics and Gerontology and Health Informatics, having authored 161 papers that have together received 4.4k indexed citations. Recurring topics across this work include Health Systems, Economic Evaluations, Quality of Life (28 papers), Machine Learning in Healthcare (23 papers), Chronic Disease Management Strategies (16 papers), Advanced Causal Inference Techniques (15 papers), Acute Myocardial Infarction Research (14 papers), Cancer Risks and Factors (11 papers), Nutritional Studies and Diet (9 papers) and Statistical Methods and Bayesian Inference (9 papers). The work is most often cited by research in Health Informatics (117 citations), Cardiology and Cardiovascular Medicine (1.1k citations), Health Information Management (193 citations), Geriatrics and Gerontology (156 citations) and Statistics and Probability (243 citations). Matthew Sperrin has collaborated with scholars based in United Kingdom, United States and Netherlands. Frequent co-authors include Iain Buchan, Andrew G. Renehan, Glen P. Martin, Hannah Lennon, Ellena Badrick, Niels Peek, Mamas A. Mamas, Evangelos Kontopantelis, Peter Ludman and Chun Shing Kwok. Their work appears in journals such as Journal of Clinical Epidemiology, BMJ Open, Statistics in Medicine, BMC Medical Research Methodology and British Journal of Cancer.

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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