James Good

735 citations
14 papers · 158 · h-index 6

Impact in

    • Cancer-related Molecular Pathways
    • PARP inhibition in cancer therapy
    • CAR-T cell therapy research
    • Pancreatic and Hepatic Oncology Research
    • COVID-19 and healthcare impacts

Papers in

James Good

11 papers receiving 157 citations

Peers

James Good
Comparison fields: 5 of 38
  • Oncology 79
  • Otorhinolaryngology 9
  • Cancer Research 23
  • Molecular Biology 64
  • Immunology 19
Replace Alessia D’Alonzo with:
Alessia D’Alonzo Italy
Tanja K. Eggersmann Germany
Grant Duclos United States
Luca Tonella Italy
Hao-Jiong Zhang China
Olivia D. Lara United States
Jeremy L. Pautu India
Ricardo P. Moura Brazil
Min Cui United States
Francesca Aroldi Italy
James Good relative to Alessia D’Alonzo Italy Alessia D’Alonzo's profile →
Citations per field
00.5×4.5×
Alessia D’Alonzo · 1×
Citations per year

Countries citing papers authored by James Good

Since Specialization
Citations

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

Fields of papers citing papers by James Good

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

14 of 14 papers shown
#Work
1 201245
2 202027
3 200524
4 202018
5 202017
6 201813
7 20214
8 20243
9 20233
10 20122
11 20232
12 20210
13 20250
14 20070

About James Good

James Good is a scholar working on Radiation, Pulmonary and Respiratory Medicine, Oncology, Radiology, Nuclear Medicine and Imaging and Hepatology, having authored 14 papers that have together received 158 indexed citations. Recurring topics across this work include Advanced Radiotherapy Techniques (4 papers), Lung Cancer Diagnosis and Treatment (3 papers), Hepatocellular Carcinoma Treatment and Prognosis (2 papers), Radiomics and Machine Learning in Medical Imaging (1 paper), DNA Repair Mechanisms (1 paper), Pancreatic and Hepatic Oncology Research (1 paper), Cancer Genomics and Diagnostics (1 paper) and Advanced X-ray and CT Imaging (1 paper). The work is most often cited by research in Oncology (79 citations), Otorhinolaryngology (9 citations), Cancer Research (23 citations), Molecular Biology (64 citations) and Immunology (19 citations). James Good has collaborated with scholars based in United Kingdom, United States and Netherlands. Frequent co-authors include Kevin J. Harrington, Shane Zaidi, Ian Collins, M. Hawkins, Marcel Verheij, Martin McLaughlin, Joan Kyula, Ned Powell, Michelle D. Garrett and Hisham Mehanna. Their work appears in journals such as BMJ Open, Journal of Clinical Oncology, Frontiers in Oncology, Technical Innovations & Patient Support in Radiation Oncology and International Journal of Radiation Oncology*Biology*Physics.

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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