Christopher R. King

129 papers receiving 4.0k citations

Christopher R. King's Hit Papers

Use of Machine Learning to Develop and Evaluate Models Using Preoperative and Intraoperative Data to Identify Risks of Postoperative Complications 2021 · 206 citations
2060+4+8Years since publication100200300

Peers

Christopher R. King
Comparison fields: 5 of 152
  • Health Informatics 94
  • Radiation 614
  • Pulmonary and Respiratory Medicine 1.9k
  • Pharmacology 188
  • Critical Care and Intensive Care Medicine 83
Replace Tatsuki Koyama with:
Tatsuki Koyama United States
Manuela Joore Netherlands
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Koon Ho Rha South Korea
Mouaz H. Al‐Mallah United States
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Citations per year

Countries citing papers authored by Christopher R. King

Since Specialization
Citations

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

Fields of papers citing papers by Christopher R. King

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Christopher R. King. 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 Christopher R. King. The network helps show where Christopher R. King may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 133 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Stereotactic body radiotherapy for localized prostate cancer: Pooled analysis from a multi-institutional consortium of prospective phase II trials
Hit paper breakdown →
2013336
2 2008285
3 2008237
4
Use of Machine Learning to Develop and Evaluate Models Using Preoperative and Intraoperative Data to Identify Risks of Postoperative Complications
Hit paper breakdown →
2021206
5 2012153
6 2001151
7 2018139
8 2004123
9 2007104
10 200894
11 200787
12 200083
13 201980
14 200078
15 200577
16 201972
17 201672
18 201070
19 200867
20 200467

About Christopher R. King

Christopher R. King is a scholar working on Pulmonary and Respiratory Medicine, Radiation, Surgery, Artificial Intelligence and Oncology, having authored 133 papers that have together received 4.1k indexed citations. Recurring topics across this work include Prostate Cancer Diagnosis and Treatment (49 papers), Advanced Radiotherapy Techniques (21 papers), Prostate Cancer Treatment and Research (19 papers), Machine Learning in Healthcare (5 papers), Bladder and Urothelial Cancer Treatments (4 papers), Intensive Care Unit Cognitive Disorders (4 papers), Hospital Admissions and Outcomes (4 papers) and Radiation Therapy and Dosimetry (4 papers). The work is most often cited by research in Health Informatics (94 citations), Radiation (614 citations), Pulmonary and Respiratory Medicine (1.9k citations), Pharmacology (188 citations) and Critical Care and Intensive Care Medicine (83 citations). Christopher R. King has collaborated with scholars based in United States, Canada and United Kingdom. Frequent co-authors include Joseph C. Presti, Harcharan Gill, Michael L. Steinberg, James D. Brooks, Jack F. Fowler, Paul J. Rathouz, Todd Pawlicki, Patrick A. Kupelian, Daniel S. Kapp and Michael S. Avidan. Their work appears in journals such as International Journal of Radiation Oncology*Biology*Physics, Journal of Clinical Oncology, Radiotherapy and Oncology, Medical Physics and CHEST Journal.

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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