Derek Driggs

1.1k citations
9 papers · 638 · 1 hit paper · h-index 5

Impact in

Papers in

Derek Driggs

8 papers receiving 622 citations

Derek Driggs's Hit Papers

Common pitfalls and recommendations for using machine learning to detect and prognosticate for COVID-19 using chest radiographs and CT scans 2020 · 580 citations
5800+2+4Years since publication100200300400500

Peers

Derek Driggs
Comparison fields: 5 of 121
  • Health Informatics 178
  • Radiology, Nuclear Medicine and Imaging 341
  • Artificial Intelligence 241
  • Computational Mathematics 4
  • Health Information Management 26
Replace Cathal McCague with:
Cathal McCague United Kingdom
Christian Etmann United Kingdom
Stephan Ursprung United Kingdom
Huan Yuan China
Julian Gilbey United Kingdom
Xiaoming Qiu China
Vaishnavi Singh India
Weixiang Chen China
Vruddhi Shah India
Derek Driggs relative to Cathal McCague United Kingdom Cathal McCague's profile →
Citations per field
00.5×1.5×
Cathal McCague · 1×
Citations per year

Countries citing papers authored by Derek Driggs

Since Specialization
Citations

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

Fields of papers citing papers by Derek Driggs

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

9 of 9 papers shown
#Work
1
Common pitfalls and recommendations for using machine learning to detect and prognosticate for COVID-19 using chest radiographs and CT scans
Hit paper breakdown →
2020580
2 201521
3 202119
4
Machine learning for COVID-19 detection and prognostication using chest radiographs and CT scans: a systematic methodological review
202010
5 20224
6 20192
7
The Roles of Age, Gender and Setting in Korean Half-talk Shift
20191
8
On the Bias-Variance Tradeoff in Stochastic Gradient Methods
20191
9 20240

About Derek Driggs

Derek Driggs is a scholar working on Computational Mechanics, Numerical Analysis, Health Informatics, Artificial Intelligence and Radiology, Nuclear Medicine and Imaging, having authored 9 papers that have together received 638 indexed citations. Recurring topics across this work include Sparse and Compressive Sensing Techniques (4 papers), Advanced Optimization Algorithms Research (3 papers), Radiomics and Machine Learning in Medical Imaging (2 papers), Artificial Intelligence in Healthcare and Education (2 papers), COVID-19 diagnosis using AI (2 papers), Stochastic Gradient Optimization Techniques (2 papers), Second Language Learning and Teaching (1 paper) and Plant Water Relations and Carbon Dynamics (1 paper). The work is most often cited by research in Health Informatics (178 citations), Radiology, Nuclear Medicine and Imaging (341 citations), Artificial Intelligence (241 citations), Computational Mathematics (4 citations) and Health Information Management (26 citations). Derek Driggs has collaborated with scholars based in United Kingdom, United States and China. Frequent co-authors include Carola‐Bibiane Schönlieb, Michael Roberts, Evis Sala, Julian Gilbey, Cathal McCague, Christian Etmann, Lucian Beer, Michael Yeung, Jonathan Weir‐McCall and Stephan Ursprung. Their work appears in journals such as SIAM Journal on Imaging Sciences, Journal of Language Identity & Education, Research Explorer (The University of Manchester), Europe PMC (PubMed Central) and arXiv (Cornell University).

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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