T. Williams

741 total citations
24 papers, 514 citations indexed

About

T. Williams is a scholar working on Oncology, Radiology, Nuclear Medicine and Imaging and Surgery. According to data from OpenAlex, T. Williams has authored 24 papers receiving a total of 514 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Oncology, 6 papers in Radiology, Nuclear Medicine and Imaging and 5 papers in Surgery. Recurrent topics in T. Williams's work include Radiomics and Machine Learning in Medical Imaging (4 papers), Image and Signal Denoising Methods (4 papers) and Bone health and treatments (4 papers). T. Williams is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (4 papers), Image and Signal Denoising Methods (4 papers) and Bone health and treatments (4 papers). T. Williams collaborates with scholars based in United States, Canada and United Kingdom. T. Williams's co-authors include Robert Li, Robert B. Darnell, Jerome B. Posner, Wendy K. Roberts, Joseph M. Huryn, Cherry L. Estilo, C. Greenfield, Paul Noone, R E Pounder and Athanasios Dousmanis and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Clinical Investigation and Journal of Clinical Oncology.

In The Last Decade

T. Williams

22 papers receiving 501 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
T. Williams United States	13	146	109	101	74	68	24	514
Sung Uk Lee South Korea	12	110 0.8×	29 0.3×	49 0.5×	45 0.6×	28 0.4×	39	518
Harry Harms Germany	16	116 0.8×	50 0.5×	144 1.4×	8 0.1×	55 0.8×	47	1.1k
Jun Aoki Japan	13	74 0.5×	11 0.1×	119 1.2×	100 1.4×	18 0.3×	21	769
Ekaterini Solomou Greece	10	92 0.6×	83 0.8×	43 0.4×	10 0.1×	11 0.2×	20	393
Fayu Liu China	14	110 0.8×	89 0.8×	51 0.5×	30 0.4×	5 0.1×	34	671
Sung Ho Yoon South Korea	10	48 0.3×	34 0.3×	55 0.5×	15 0.2×	21 0.3×	63	722
Matteo Mario Bonsanto Germany	15	109 0.7×	46 0.4×	238 2.4×	163 2.2×	4 0.1×	51	900
Christof Seiler Switzerland	13	68 0.5×	75 0.7×	33 0.3×	5 0.1×	22 0.3×	32	409
Tim Lee Canada	12	316 2.2×	59 0.5×	89 0.9×	34 0.5×	3 0.0×	28	682
Steven J. Esses United States	9	86 0.6×	50 0.5×	149 1.5×	9 0.1×	6 0.1×	12	700

Countries citing papers authored by T. Williams

Since Specialization

Citations

This map shows the geographic impact of T. Williams'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 T. Williams with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites T. Williams more than expected).

Fields of papers citing papers by T. Williams

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of T. Williams

This figure shows the co-authorship network connecting the top 25 collaborators of T. Williams. A scholar is included among the top collaborators of T. Williams 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 T. Williams. T. Williams is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

1.

Williams, T., Mithat Gönen, Rick Wray, Richard Kinh Gian, & Amber L. Simpson. (2023). Quantitation of Oncologic Image Features for Radiomic Analyses in PET. Methods in molecular biology. 2729. 409–421.

2.

White, Nicola, Sharon A. Appleyard, Sarah Bauerle Bass, et al.. (2021). A Short Report Examining the Introduction of Routine Use of Patient-Reported Outcome Measures in a Mixed Oncology Population. Clinical Oncology. 34(4). 241–246. 6 indexed citations

3.

Williams, T., et al.. (2020). PO-0949: Maximising patient access to advanced breast radiotherapy techniques and personalised radiotherapy. Radiotherapy and Oncology. 152. S507–S507. 1 indexed citations

4.

Williams, T., Sharon Lawrence, Jayasree Chakraborty, et al.. (2020). A combined radiomics and cyst fluid inflammatory markers model to predict preoperative risk in pancreatic cystic lesions. 110–110. 1 indexed citations

5.

Williams, T., Sharon Lawrence, Jayasree Chakraborty, et al.. (2020). Multimodal radiomics and cyst fluid inflammatory markers model to predict preoperative risk in intraductal papillary mucinous neoplasms. Journal of Medical Imaging. 7(3). 1–1. 9 indexed citations

6.

Roberts, Sheryl, Chrysafis Andreou, Susanne Kossatz, et al.. (2019). Acid specific dark quencher QC1 pHLIP for multi-spectral optoacoustic diagnoses of breast cancer. Scientific Reports. 9(1). 8550–8550. 19 indexed citations

7.

Williams, T. & Robert Li. (2018). Wavelet Pooling for Convolutional Neural Networks. International Conference on Learning Representations. 87 indexed citations

8.

Williams, T. & Robert Li. (2018). An Ensemble of Convolutional Neural Networks Using Wavelets for Image Classification. Journal of Software Engineering and Applications. 11(2). 69–88. 16 indexed citations

9.

Stindel, Éric, Fanny Lanternier, T. Williams, et al.. (2017). Miltefosine-based regimen as salvage therapy in Lomentospora prolificans bone and joint infection. Médecine et Maladies Infectieuses. 48(1). 63–65. 12 indexed citations

10.

Querellou, S., et al.. (2016). Pathologies prothétiques de hanche : intérêt de la médecine nucléaire. Médecine Nucléaire. 40(6). 404–410.

11.

Williams, T. & Robert Li. (2016). SDA-based neural network approach to digit classification. 1–6. 2 indexed citations

12.

Williams, T. & Robert Li. (2016). An efficient hybrid Fourier-Wavelet Neighborhood Coefficient image denoising approach. 90. 1–4. 1 indexed citations

13.

Hocker, James R., Russell G. Postier, Min Li, et al.. (2015). Discriminating patients with early-stage pancreatic cancer or chronic pancreatitis using serum electrospray mass profiling. Cancer Letters. 359(2). 314–324. 17 indexed citations

14.

Lenoir, H., et al.. (2013). Free vascularized fibular graft as a salvage procedure for large clavicular defect: A two cases report. Orthopaedics & Traumatology Surgery & Research. 99(7). 859–863. 19 indexed citations

15.

Heath, Simon, Van C. Willis, Karin J. Purdie, et al.. (2011). Clinically Significant Human Papilloma Virus in Squamous Cell Carcinoma of the Head and Neck in UK Practice. Clinical Oncology. 24(1). e18–e23. 36 indexed citations

16.

Roberts, Wendy K., John J. Fak, T. Williams, et al.. (2009). Patients with lung cancer and paraneoplastic Hu syndrome harbor HuD-specific type 2 CD8+ T cells. Journal of Clinical Investigation. 119(7). 2042–51. 75 indexed citations

17.

Santomasso, Bianca, Wendy K. Roberts, T. Williams, et al.. (2007). A T cell receptor associated with naturally occurring human tumor immunity. Proceedings of the National Academy of Sciences. 104(48). 19073–19078. 29 indexed citations

18.

Estilo, Cherry L., et al.. (2004). Osteonecrosis of the maxilla and mandible in patients treated with bisphosphonates: A retrospective study. Journal of Clinical Oncology. 22(14_suppl). 8088–8088. 20 indexed citations

19.

Estilo, Cherry L., et al.. (2004). Osteonecrosis of the maxilla and mandible in patients treated with bisphosphonates: A retrospective study. Journal of Clinical Oncology. 22(14_suppl). 8088–8088. 33 indexed citations

20.

Greenfield, C., et al.. (1983). Clostridium difficile and inflammatory bowel disease.. Gut. 24(8). 713–717. 57 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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