Gilmer Valdés

3.5k total citations · 1 hit paper
59 papers, 2.0k citations indexed

About

Gilmer Valdés is a scholar working on Radiology, Nuclear Medicine and Imaging, Radiation and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Gilmer Valdés has authored 59 papers receiving a total of 2.0k indexed citations (citations by other indexed papers that have themselves been cited), including 38 papers in Radiology, Nuclear Medicine and Imaging, 30 papers in Radiation and 22 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Gilmer Valdés's work include Advanced Radiotherapy Techniques (30 papers), Radiomics and Machine Learning in Medical Imaging (21 papers) and Lung Cancer Diagnosis and Treatment (12 papers). Gilmer Valdés is often cited by papers focused on Advanced Radiotherapy Techniques (30 papers), Radiomics and Machine Learning in Medical Imaging (21 papers) and Lung Cancer Diagnosis and Treatment (12 papers). Gilmer Valdés collaborates with scholars based in United States, Canada and Netherlands. Gilmer Valdés's co-authors include Timothy D. Solberg, Olivier Morin, Charles B. Simone, Vasant Kearney, Ryan Scheuermann, Maria F. Chan, Lyle Ungar, Sue S. Yom, Alon Witztum and José Marcio Luna and has published in prestigious journals such as Proceedings of the National Academy of Sciences, PLoS ONE and IEEE Transactions on Pattern Analysis and Machine Intelligence.

In The Last Decade

Gilmer Valdés

56 papers receiving 1.9k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Artificial intelligence and machine learning for medical imaging: A technology review

2021 236 citations Ana María Barragán Montero, Umair Javaid et al. Physica Medica profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Gilmer Valdés United States	24	1.3k	880	604	490	348	59	2.0k
Mark J. Gooding United Kingdom	21	1.1k 0.9×	781 0.9×	453 0.8×	378 0.8×	252 0.7×	64	1.6k
Jason Dowling Australia	24	1.7k 1.3×	1.1k 1.3×	662 1.1×	550 1.1×	381 1.1×	129	2.7k
Liyuan Chen China	22	833 0.6×	423 0.5×	376 0.6×	321 0.7×	266 0.8×	89	1.5k
Isaac Shiri Switzerland	36	2.9k 2.2×	299 0.3×	1.4k 2.3×	860 1.8×	544 1.6×	174	3.6k
Tyler Bradshaw United States	19	1.1k 0.9×	179 0.2×	372 0.6×	276 0.6×	119 0.3×	63	1.4k
Lois Holloway Australia	28	2.6k 2.0×	2.2k 2.5×	623 1.0×	1.5k 3.1×	448 1.3×	260	4.1k
Lei Ren United States	25	1.5k 1.2×	1.1k 1.3×	659 1.1×	632 1.3×	119 0.3×	138	2.1k
Lisanne V. van Dijk Netherlands	23	1.3k 1.0×	669 0.8×	279 0.5×	641 1.3×	149 0.4×	89	1.9k
Annette Haworth Australia	28	1.4k 1.1×	1.5k 1.7×	387 0.6×	1.4k 2.8×	230 0.7×	143	2.7k
Avishek Chatterjee Netherlands	17	815 0.6×	121 0.1×	247 0.4×	283 0.6×	340 1.0×	38	1.2k

Countries citing papers authored by Gilmer Valdés

Since Specialization

Citations

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

Fields of papers citing papers by Gilmer Valdés

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Gilmer Valdés

This figure shows the co-authorship network connecting the top 25 collaborators of Gilmer Valdés. A scholar is included among the top collaborators of Gilmer Valdés based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Gilmer Valdés. Gilmer Valdés is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Schnipper, Jeffrey L., Colin C. Hubbard, Nader Najafi, et al.. (2024). Analysis of Clinical Criteria for Discharge Among Patients Hospitalized for COVID-19: Development and Validation of a Risk Prediction Model. Journal of General Internal Medicine. 39(14). 2649–2661. 3 indexed citations

Chow, Ronald, Shaakir Hasan, Chenxi Gao, et al.. (2024). The Accuracy of Artificial Intelligence ChatGPT in Oncology Examination Questions. Journal of the American College of Radiology. 21(11). 1800–1804. 10 indexed citations

Lichter, Katie, et al.. (2023). A Machine Learning Framework Integrating Electronic Health Records for Survival Prognostication in Cervix Cancer. International Journal of Radiation Oncology*Biology*Physics. 117(2). e529–e529. 1 indexed citations

Valdés, Gilmer, et al.. (2023). A unified path seeking algorithm for IMRT and IMPT beam orientation optimization. Physics in Medicine and Biology. 68(19). 195011–195011.

Tilki, Derya, Jean Feng, Hartwig Huland, et al.. (2023). Multi-institutional Development and External Validation of a Machine Learning Model for the Prediction of Distant Metastasis in Patients Treated by Salvage Radiotherapy for Biochemical Failure After Radical Prostatectomy. European Urology Focus. 10(1). 66–74. 3 indexed citations

Lafrenière, M., Gilmer Valdés, & Martina Descovich. (2023). Predicting successful clinical candidates for fiducial‐free lung tumor tracking with a deep learning binary classification model. Journal of Applied Clinical Medical Physics. 24(12). e14146–e14146. 3 indexed citations

Valdés, Gilmer & Lei Xing. (2023). Artificial Intelligence in Radiation Oncology and Biomedical Physics. 2 indexed citations

Montero, Ana María Barragán, Adrien Bibal, Gilmer Valdés, et al.. (2022). Towards a safe and efficient clinical implementation of machine learning in radiation oncology by exploring model interpretability, explainability and data-model dependency. Physics in Medicine and Biology. 67(11). 11TR01–11TR01. 48 indexed citations

Valdés, Gilmer, et al.. (2022). NSMCE2, a novel super-enhancer-regulated gene, is linked to poor prognosis and therapy resistance in breast cancer. BMC Cancer. 22(1). 1056–1056. 7 indexed citations

10.

Morin, Olivier, et al.. (2022). Prospective Clinical Validation of Virtual Patient-Specific Quality Assurance of Volumetric Modulated Arc Therapy Radiation Therapy Plans. International Journal of Radiation Oncology*Biology*Physics. 113(5). 1091–1102. 24 indexed citations

11.

Montero, Ana María Barragán, Umair Javaid, Gilmer Valdés, et al.. (2021). Artificial intelligence and machine learning for medical imaging: A technology review. Physica Medica. 83. 242–256. 236 indexed citations breakdown →

12.

Wu, Susan, Anthony Wong, Katsuto Shinohara, et al.. (2021). Salvage High-Dose-Rate Brachytherapy for Recurrent Prostate Cancer After Definitive Radiation. Practical Radiation Oncology. 11(6). 515–526. 10 indexed citations

13.

Luo, Yi, Shruti Jolly, David A. Palma, et al.. (2021). A situational awareness Bayesian network approach for accurate and credible personalized adaptive radiotherapy outcomes prediction in lung cancer patients. Physica Medica. 87. 11–23. 12 indexed citations

14.

Luna, José Marcio, Efstathios D. Gennatas, Lyle Ungar, et al.. (2019). Building more accurate decision trees with the additive tree. Proceedings of the National Academy of Sciences. 116(40). 19887–19893. 50 indexed citations

15.

Interian, Yannet, et al.. (2019). Training Deep Learning models with small datasets.. arXiv (Cornell University). 7 indexed citations

16.

Luna, José Marcio, Hann‐Hsiang Chao, Eric S. Diffenderfer, et al.. (2019). Predicting radiation pneumonitis in locally advanced stage II–III non-small cell lung cancer using machine learning. Radiotherapy and Oncology. 133. 106–112. 69 indexed citations

17.

Valdés, Gilmer, José Marcio Luna, Eric Eaton, et al.. (2016). MediBoost: a Patient Stratification Tool for Interpretable Decision Making in the Era of Precision Medicine. Scientific Reports. 6(1). 37854–37854. 75 indexed citations

18.

Valdés, Gilmer, et al.. (2016). Using machine learning to predict radiation pneumonitis in patients with stage I non-small cell lung cancer treated with stereotactic body radiation therapy. Physics in Medicine and Biology. 61(16). 6105–6120. 78 indexed citations

19.

Valdés, Gilmer, et al.. (2015). Use of TrueBeam developer mode for imaging QA. Journal of Applied Clinical Medical Physics. 16(4). 322–333. 30 indexed citations

20.

Valdés, Gilmer & Keisuke S. Iwamoto. (2013). Re-evaluation of cellular radiosensitization by 5-fluorouracil: High-dose, pulsed administration is effective and preferable to conventional low-dose, chronic administration. International Journal of Radiation Biology. 89(10). 851–862. 7 indexed citations

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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