Mark Cicero

1.5k total citations
7 papers, 633 citations indexed

About

Mark Cicero is a scholar working on Radiology, Nuclear Medicine and Imaging, Health Informatics and Orthopedics and Sports Medicine. According to data from OpenAlex, Mark Cicero has authored 7 papers receiving a total of 633 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Radiology, Nuclear Medicine and Imaging, 3 papers in Health Informatics and 2 papers in Orthopedics and Sports Medicine. Recurrent topics in Mark Cicero's work include Radiomics and Machine Learning in Medical Imaging (3 papers), Artificial Intelligence in Healthcare and Education (3 papers) and Bone health and osteoporosis research (2 papers). Mark Cicero is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (3 papers), Artificial Intelligence in Healthcare and Education (3 papers) and Bone health and osteoporosis research (2 papers). Mark Cicero collaborates with scholars based in Canada, United States and Brazil. Mark Cicero's co-authors include Alexander Bilbily, Bruce Gray, Kuhan Perampaladas, Errol Colak, Joseph Barfett, Katherine P. Andriole, Ian Pan, Hans Henrik Thodberg, Luciano M. Prevedello and Jayashree Kalpathy–Cramer and has published in prestigious journals such as Radiology, Investigative Radiology and Journal of the American College of Radiology.

In The Last Decade

Mark Cicero

6 papers receiving 621 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Mark Cicero Canada	6	395	221	131	126	120	7	633
Alexander Bilbily Canada	6	313 0.8×	127 0.6×	104 0.8×	96 0.8×	119 1.0×	14	527
Rafael T. Sousa Brazil	3	203 0.5×	101 0.5×	63 0.5×	65 0.5×	117 1.0×	8	335
Shankeeth Vinayahalingam Netherlands	14	179 0.5×	118 0.5×	221 1.7×	127 1.0×	36 0.3×	55	719
Sebastian Tschauner Austria	13	186 0.5×	96 0.4×	120 0.9×	59 0.5×	23 0.2×	45	411
Sven Koitka Germany	12	124 0.3×	43 0.2×	55 0.4×	87 0.7×	26 0.2×	28	317
Alexis Ducarouge France	7	292 0.7×	304 1.4×	176 1.3×	31 0.2×	11 0.1×	11	485
Haihua Zhu China	15	129 0.3×	31 0.1×	161 1.2×	86 0.7×	30 0.3×	40	711
Félix Paulano‐Godino Spain	7	128 0.3×	88 0.4×	119 0.9×	69 0.5×	6 0.1×	19	329
Robert Hotchkiss United States	5	257 0.7×	297 1.3×	237 1.8×	70 0.6×	7 0.1×	6	593
Amir H. Abdi Canada	10	167 0.4×	14 0.1×	96 0.7×	67 0.5×	11 0.1×	23	392

Countries citing papers authored by Mark Cicero

Since Specialization

Citations

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

Fields of papers citing papers by Mark Cicero

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mark Cicero

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

All Works

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7 of 7 papers shown

Bilbily, Alexander, Catriona Syme, Jonathan D. Adachi, et al.. (2023). Opportunistic Screening of Low Bone Mineral Density From Standard X-Rays. Journal of the American College of Radiology. 21(4). 633–639. 9 indexed citations

Golestan, Keyvan, Catriona Syme, Alexander Bilbily, et al.. (2023). Approximating femoral neck bone mineral density from hand, knee, and pelvis X-rays using deep learning. 6. 7–7.

Parker, William, Jacob L. Jaremko, Mark Cicero, et al.. (2020). Canadian Association of Radiologists White Paper on De-Identification of Medical Imaging: Part 1, General Principles. Canadian Association of Radiologists Journal. 72(1). 13–24. 10 indexed citations

Parker, William, Jacob L. Jaremko, Mark Cicero, et al.. (2020). Canadian Association of Radiologists White Paper on De-identification of Medical Imaging: Part 2, Practical Considerations. Canadian Association of Radiologists Journal. 72(1). 25–34. 14 indexed citations

Jaremko, Jacob L., Marleine Azar, Andrea Lum, et al.. (2019). Canadian Association of Radiologists White Paper on Ethical and Legal Issues Related to Artificial Intelligence in Radiology. Canadian Association of Radiologists Journal. 70(2). 107–118. 126 indexed citations

Halabi, Safwan S., Luciano M. Prevedello, Jayashree Kalpathy–Cramer, et al.. (2018). The RSNA Pediatric Bone Age Machine Learning Challenge. Radiology. 290(2). 498–503. 283 indexed citations

Cicero, Mark, Alexander Bilbily, Errol Colak, et al.. (2016). Training and Validating a Deep Convolutional Neural Network for Computer-Aided Detection and Classification of Abnormalities on Frontal Chest Radiographs. Investigative Radiology. 52(5). 281–287. 191 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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