Phillip Chlap
Impact in
- Health Informatics top 5%
-
- Radiomics and Machine Learning in Medical Imaging
- COVID-19 diagnosis using AI
- Medical Imaging Techniques and Applications
Papers in
-
- Lung Cancer Diagnosis and Treatment 9
- Prostate Cancer Diagnosis and Treatment 4
-
- Radiomics and Machine Learning in Medical Imaging 13
- Medical Imaging Techniques and Applications 4
- Co-authors
- Lois Holloway (22 shared papers)Jason Dowling (9 shared papers)Hang Min (4 shared papers)Annette Haworth (5 shared papers)Michael Jameson (9 shared papers)Shalini Vinod (12 shared papers)Geoff P. Delaney (6 shared papers)David Thwaites (3 shared papers)
- Journals
- Radiotherapy and Oncology (9 papers)Clinical Oncology (3 papers)Physics in Medicine and Biology (2 papers)Medical Physics (1 paper)Cell Reports (1 paper)
- Partner nations
- AustraliaUnited StatesUnited Kingdom
In The Last Decade
Phillip Chlap
30 papers receiving 844 citations
Phillip Chlap's Hit Papers
Peers
Comparison fields: 5 of 129
- Health Informatics 33
- Radiology, Nuclear Medicine and Imaging 281
- Radiation 89
- Neurology 73
- Computer Vision and Pattern Recognition 176
Countries citing papers authored by Phillip Chlap
This map shows the geographic impact of Phillip Chlap'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 Phillip Chlap with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Phillip Chlap more than expected).
Fields of papers citing papers by Phillip Chlap
This network shows the impact of papers produced by Phillip Chlap. 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 Phillip Chlap. The network helps show where Phillip Chlap may publish in the future.
Co-authors
The 25 scholars most cited alongside Phillip Chlap, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 33 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | A review of medical image data augmentation techniques for deep learning applications Hit paper breakdown → | 2021 | 622 |
| 2 | 2022 | 28 | |
| 3 | 2021 | 27 | |
| 4 | 2018 | 26 | |
| 5 | 2023 | 22 | |
| 6 | 2023 | 18 | |
| 7 | 2023 | 14 | |
| 8 | 2023 | 13 | |
| 9 | 2021 | 11 | |
| 10 | 2023 | 9 | |
| 11 | 2023 | 9 | |
| 12 | 2023 | 8 | |
| 13 | 2022 | 7 | |
| 14 | 2022 | 5 | |
| 15 | 2020 | 5 | |
| 16 | 2021 | 5 | |
| 17 | 2024 | 4 | |
| 18 | 2023 | 4 | |
| 19 | 2024 | 3 | |
| 20 | 2023 | 3 |
About Phillip Chlap
Phillip Chlap is a scholar working on Pulmonary and Respiratory Medicine, Radiology, Nuclear Medicine and Imaging, Radiation, Artificial Intelligence and Biomedical Engineering, having authored 33 papers that have together received 858 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (13 papers), Advanced Radiotherapy Techniques (12 papers), Lung Cancer Diagnosis and Treatment (9 papers), Medical Imaging Techniques and Applications (4 papers), Prostate Cancer Diagnosis and Treatment (4 papers), AI in cancer detection (4 papers), Advanced X-ray and CT Imaging (2 papers) and Head and Neck Cancer Studies (2 papers). The work is most often cited by research in Health Informatics (33 citations), Radiology, Nuclear Medicine and Imaging (281 citations), Radiation (89 citations), Neurology (73 citations) and Computer Vision and Pattern Recognition (176 citations). Phillip Chlap has collaborated with scholars based in Australia, United States and United Kingdom. Frequent co-authors include Lois Holloway, Jason Dowling, Hang Min, Annette Haworth, Michael Jameson, Shalini Vinod, Geoff P. Delaney, David Thwaites, Ali Haidar and James Otton. Their work appears in journals such as Radiotherapy and Oncology, Clinical Oncology, Physics in Medicine and Biology, Medical Physics and Cell Reports.
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.