Daniel Slade

500 citations
23 papers · 185 indexed · h-index 8

Impact in

  • Hematology top 10%
    • Acute Myeloid Leukemia Research
    • Chronic Myeloid Leukemia Treatments
    • Hematopoietic Stem Cell Transplantation
    • Statistical Methods in Clinical Trials

Papers in

Daniel Slade

22 papers receiving 173 citations

Peers

Daniel Slade
Comparison fields: 5 of 66
  • Hematology 79
  • Statistics and Probability 28
  • Genetics 36
  • Rheumatology 25
  • Statistics, Probability and Uncertainty 9
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Citations per field
00.5×4.5×
Michael J. Martens · 1×
Citations per year

Countries citing papers authored by Daniel Slade

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Slade

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 23 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201951
2 202027
3 202120
4 201914
5 196311
6 20229
7 20209
8 20157
9 19987
10 20195
11 20213
12 20223
13 19553
14 19523
15 20242
16
How to transform infrastructure decision making in the UK
20182
17 20192
18
poisson: Simulating Homogenous & Non-Homogenous Poisson Processes
20152
19 20122
20
Dose Transition Pathways for Continual Reassessment Method [R package dtpcrm version 0.1.1]
20191

About Daniel Slade

Daniel Slade is a scholar working on Hematology, Statistics and Probability, Genetics, Management Science and Operations Research and Urology, having authored 23 papers that have together received 185 indexed citations. Recurring topics across this work include Acute Lymphoblastic Leukemia research (4 papers), Chronic Myeloid Leukemia Treatments (4 papers), Statistical Methods in Clinical Trials (3 papers), Chronic Lymphocytic Leukemia Research (2 papers), Colorectal and Anal Carcinomas (2 papers), Cervical Cancer and HPV Research (2 papers), Optimal Experimental Design Methods (2 papers) and Long-Term Effects of COVID-19 (1 paper). The work is most often cited by research in Hematology (79 citations), Statistics and Probability (28 citations), Genetics (36 citations), Rheumatology (25 citations) and Statistics, Probability and Uncertainty (9 citations). Daniel Slade has collaborated with scholars based in United Kingdom, United States and Germany. Frequent co-authors include Kristian Brock, Simon Gates, Christina Yap, Elizabeth Ryan, Charles Craddock, Rachel Wheat, Andrea Hodgkinson, Shamyla Siddique, Jamie Cavenagh and Wendy Ingram. Their work appears in journals such as BMJ Open, BMC Medical Research Methodology, Blood, European Journal of Paediatric Neurology and The Lancet Haematology.

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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