M Wallis

768 total citations
31 papers, 505 citations indexed

About

M Wallis is a scholar working on Oncology, Pathology and Forensic Medicine and Artificial Intelligence. According to data from OpenAlex, M Wallis has authored 31 papers receiving a total of 505 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Oncology, 10 papers in Pathology and Forensic Medicine and 8 papers in Artificial Intelligence. Recurrent topics in M Wallis's work include Global Cancer Incidence and Screening (18 papers), Breast Lesions and Carcinomas (10 papers) and AI in cancer detection (8 papers). M Wallis is often cited by papers focused on Global Cancer Incidence and Screening (18 papers), Breast Lesions and Carcinomas (10 papers) and AI in cancer detection (8 papers). M Wallis collaborates with scholars based in United Kingdom, Ireland and Switzerland. M Wallis's co-authors include R G Blanks, Kenneth C. Young, Sue Moss, Michael T. Walsh, Rosalind Given-Wilson, Sylvia O’Keeffe, KM Taylor, P.D. Britton, S. Barter and R. Sinnatamby and has published in prestigious journals such as Journal of Clinical Oncology, Cancer Research and British Journal of Cancer.

In The Last Decade

M Wallis

30 papers receiving 476 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
M Wallis United Kingdom	13	249	193	139	137	133	31	505
Todd E. Wilson United States	15	205 0.8×	203 1.1×	158 1.1×	146 1.1×	197 1.5×	20	651
Dione M. Farria United States	13	190 0.8×	103 0.5×	119 0.9×	90 0.7×	136 1.0×	22	456
L.J. Yeoman United Kingdom	14	186 0.7×	181 0.9×	107 0.8×	234 1.7×	278 2.1×	24	646
Hildegard Toth United States	6	169 0.7×	134 0.7×	158 1.1×	103 0.8×	113 0.8×	6	397
F. Baum Germany	11	128 0.5×	233 1.2×	223 1.6×	61 0.4×	124 0.9×	23	608
MJ Michell United Kingdom	13	207 0.8×	150 0.8×	121 0.9×	247 1.8×	322 2.4×	39	658
Volker Duda Germany	11	107 0.4×	141 0.7×	85 0.6×	170 1.2×	260 2.0×	41	525
Ellen Shaw de Paredes United States	15	218 0.9×	202 1.0×	130 0.9×	232 1.7×	334 2.5×	30	719
Mary Rickard Australia	17	378 1.5×	359 1.9×	350 2.5×	196 1.4×	153 1.2×	60	882
Rebecca Leddy United States	10	136 0.5×	110 0.6×	109 0.8×	169 1.2×	194 1.5×	21	454

Countries citing papers authored by M Wallis

Since Specialization

Citations

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

Fields of papers citing papers by M Wallis

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of M Wallis

This figure shows the co-authorship network connecting the top 25 collaborators of M Wallis. A scholar is included among the top collaborators of M Wallis 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 M Wallis. M Wallis 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

Taylor, Kathryn M., et al.. (2019). Evidence for avoiding the biopsy of typical fibroadenomas in women aged 25–29 years. Clinical Radiology. 74(9). 676–681. 6 indexed citations

Blanks, R G, et al.. (2019). An analysis of 11.3 million screening tests examining the association between recall and cancer detection rates in the English NHS breast cancer screening programme. European Radiology. 29(7). 3812–3819. 7 indexed citations

Blanks, R G, Rosalind Given-Wilson, Rupert Alison, Jacquie Jenkins, & M Wallis. (2019). An analysis of 11.3 million screening tests examining the association between needle biopsy rates and cancer detection rates in the English NHS Breast Cancer Screening Programme. Clinical Radiology. 74(5). 384–389. 8 indexed citations

Zia, Muhammad, et al.. (2019). P83 Evans syndrome with abdominal discomfort: a case report. Abstracts. A189.2–A189. 1 indexed citations

Sharma, Nisha, R. G. Newcombe, Monika Kaushik, et al.. (2018). Axillary tumour burden in women with one abnormal node on ultrasound compared to women with multiple abnormal nodes. Clinical Radiology. 73(4). 391–395. 8 indexed citations

Fallowfield, Lesley, et al.. (2018). Abstract OT3-08-01: Interview data from women contemplating LORIS trial entry during the feasibility study. Cancer Research. 78(4_Supplement). OT3–8. 1 indexed citations

Wallis, M, Fleur Kilburn‐Toppin, & Sian Taylor‐Phillips. (2017). Does preoperative axillary staging lead to overtreatment of women with screen-detected breast cancer?. Clinical Radiology. 73(5). 467–472. 8 indexed citations

Duffy, SW, James Mackay, Susan N. Thomas, et al.. (2013). Evaluation of mammographic surveillance services in women aged 40–49 years with a moderate family history of breast cancer: a single-arm cohort study. Health Technology Assessment. 17(11). vii–xiv, 1. 12 indexed citations

Warwick, Jane, M Wallis, Sylvia O’Keeffe, et al.. (2012). Measuring the accuracy of diagnostic imaging in symptomatic breast patients: team and individual performance. British Journal of Radiology. 85(1012). 415–422. 24 indexed citations

10.

Taylor, KM, P.D. Britton, Sylvia O’Keeffe, & M Wallis. (2011). Quantification of the UK 5-point breast imaging classification and mapping to BI-RADS to facilitate comparison with international literature. British Journal of Radiology. 84(1007). 1005–1010. 23 indexed citations

11.

Britton, P.D., Penelope Moyle, John R. Benson, et al.. (2010). Ultrasound of the axilla: where to look for the sentinel lymph node. Clinical Radiology. 65(5). 373–376. 20 indexed citations

12.

Duffy, S W, R. Sinnatamby, M Wallis, et al.. (2009). One-stop diagnostic breast clinics: how often are breast cancers missed?. British Journal of Cancer. 100(12). 1873–1878. 25 indexed citations

13.

Wallis, M, et al.. (2008). Do screen-detected lobular and ductal carcinoma present with different mammographic features?. British Journal of Radiology. 82(973). 20–27. 10 indexed citations

14.

Brace, C. Loring, et al.. (2006). Digital mammography: the human factors implications. Breast Cancer Research. 8(S1). 2 indexed citations

15.

Young, Kenneth C., et al.. (1999). Analysis of optical density and contrast in mammograms.. British Journal of Radiology. 72(859). 670–677. 9 indexed citations

16.

Young, Kenneth C., M Wallis, R G Blanks, & Sue Moss. (1997). Influence of number of views and mammographic film density on the detection of invasive cancers: results from the NHS Breast Screening Programme.. British Journal of Radiology. 70(833). 482–488. 32 indexed citations

17.

Young, Kenneth C., et al.. (1994). Mammographic film density and detection of small breast cancers. Clinical Radiology. 49(7). 461–465. 59 indexed citations

18.

Wallis, M, et al.. (1993). Complex sclerosing lesions (radial scars) of the breast can be palpable. Clinical Radiology. 48(5). 319–320. 19 indexed citations

19.

Wallis, M, et al.. (1991). A review of false negative mammography in a symptomatic population. Clinical Radiology. 44(1). 13–15. 71 indexed citations

20.

Wallis, M. (1989). Are three views necessary to examine acute ankle injuries?. Clinical Radiology. 40(4). 424–425. 11 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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