Dave Lowe

489 citations
4 papers · 371 · 1 hit paper · h-index 3

Impact in

Papers in

    • Renal Transplantation Outcomes and Treatments 3
    • Transplantation: Methods and Outcomes 1
    • Organ Transplantation Techniques and Outcomes 1

Dave Lowe

4 papers receiving 365 citations

Dave Lowe's Hit Papers

Decision tree and random forest models for outcome prediction in antibody incompatible kidney transplantation 2017 · 276 citations
2760+3+6Years since publication50100150200250

Peers

Dave Lowe
Comparison fields: 5 of 134
  • Health Informatics 14
  • Transplantation 21
  • Health Information Management 37
  • Artificial Intelligence 83
  • Biophysics 9
Replace Natasha Khovanova with:
Natasha Khovanova United Kingdom
Torgyn Shaikhina United Kingdom
Junhyug Noh South Korea
M. Cruz-Ramírez Spain
Emine Cengil Türkiye
Ivan Stojković United States
Shuang Liang China
Wilson E. Marcílio-Jr Brazil
Guolong Cai China
Dave Lowe relative to Natasha Khovanova United Kingdom Natasha Khovanova's profile →
Citations per field
00.5×1.5×
Natasha Khovanova · 1×
Citations per year

Countries citing papers authored by Dave Lowe

Since Specialization
Citations

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

Fields of papers citing papers by Dave Lowe

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 13 scholars most cited alongside Dave Lowe, 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 Dave Lowe Line = papers co-authored together Dave Lowe links everyone, so they are left out of the graph.

All Works

4 of 4 papers shown
#Work
1
Decision tree and random forest models for outcome prediction in antibody incompatible kidney transplantation
Hit paper breakdown →
2017276
2 201589
3 20244
4 20242

About Dave Lowe

Dave Lowe is a scholar working on Transplantation, Surgery, Immunology, Health Information Management and Radiology, Nuclear Medicine and Imaging, having authored 4 papers that have together received 371 indexed citations. Recurring topics across this work include Renal Transplantation Outcomes and Treatments (3 papers), T-cell and B-cell Immunology (2 papers), Transplantation: Methods and Outcomes (1 paper), Hepatitis C virus research (1 paper), Organ Transplantation Techniques and Outcomes (1 paper), Artificial Intelligence in Healthcare (1 paper) and Monoclonal and Polyclonal Antibodies Research (1 paper). The work is most often cited by research in Health Informatics (14 citations), Transplantation (21 citations), Health Information Management (37 citations), Artificial Intelligence (83 citations) and Biophysics (9 citations). Dave Lowe has collaborated with scholars based in Japan, France and United Kingdom. Frequent co-authors include Robert Higgins, Sunil Daga, Torgyn Shaikhina, David Briggs, Natasha Khovanova, Hiroko Miyadera, Olivier Toutirais, Jar-How Lee, Julien Lion and Nuala Mooney. Their work appears in journals such as The Journal of Immunology, Biomedical Signal Processing and Control, HLA and IFAC-PapersOnLine.

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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