Mohammad Peikari

430 total citations
13 papers, 276 citations indexed

About

Mohammad Peikari is a scholar working on Artificial Intelligence, Radiology, Nuclear Medicine and Imaging and Computer Vision and Pattern Recognition. According to data from OpenAlex, Mohammad Peikari has authored 13 papers receiving a total of 276 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Artificial Intelligence, 6 papers in Radiology, Nuclear Medicine and Imaging and 5 papers in Computer Vision and Pattern Recognition. Recurrent topics in Mohammad Peikari's work include AI in cancer detection (7 papers), Digital Imaging for Blood Diseases (4 papers) and Ultrasound Imaging and Elastography (3 papers). Mohammad Peikari is often cited by papers focused on AI in cancer detection (7 papers), Digital Imaging for Blood Diseases (4 papers) and Ultrasound Imaging and Elastography (3 papers). Mohammad Peikari collaborates with scholars based in Canada and United States. Mohammad Peikari's co-authors include Anne L. Martel, Sharon Nofech‐Mozes, Sherine Salama, Mehrdad J. Gangeh, Judit Zubovits, G. Clarke, Shazia Akbar, Gábor Fichtinger, Everette C. Burdette and Tamas Heffter and has published in prestigious journals such as Journal of the American College of Cardiology, Scientific Reports and European Heart Journal.

In The Last Decade

Mohammad Peikari

12 papers receiving 268 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Mohammad Peikari Canada	7	175	125	94	42	31	13	276
Marek Wodziński Poland	12	193 1.1×	163 1.3×	81 0.9×	39 0.9×	66 2.1×	48	469
Marek Kowal Poland	12	343 2.0×	227 1.8×	223 2.4×	60 1.4×	32 1.0×	27	530
Christoph Baur Germany	5	322 1.8×	197 1.6×	143 1.5×	38 0.9×	36 1.2×	8	458
Min Beom Lee South Korea	8	146 0.8×	153 1.2×	175 1.9×	19 0.5×	24 0.8×	11	376
Soroosh Tayebi Arasteh Germany	10	185 1.1×	217 1.7×	84 0.9×	9 0.2×	35 1.1×	25	455
Wenqi Lu United Kingdom	11	167 1.0×	203 1.6×	228 2.4×	55 1.3×	109 3.5×	19	486
Kerem Can Tezcan Switzerland	7	91 0.5×	164 1.3×	45 0.5×	17 0.4×	38 1.2×	8	271
Tianyu Shi China	9	153 0.9×	207 1.7×	168 1.8×	13 0.3×	47 1.5×	16	405

Countries citing papers authored by Mohammad Peikari

Since Specialization

Citations

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

Fields of papers citing papers by Mohammad Peikari

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mohammad Peikari

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

All Works

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13 of 13 papers shown

Yu, Christopher, Mohammad Peikari, Chun‐Po Steve Fan, Caroline McIntosh, & Paaladinesh Thavendiranathan. (2024). Prediction of cancer therapy related cardiac dysfunction by using a machine learning approach with cardiac magnetic resonance images. European Heart Journal. 45(Supplement_1). 1 indexed citations

Ross, Heather J., Mohammad Peikari, Julie K.K. Vishram‐Nielsen, et al.. (2024). Predicting heart failure outcomes by integrating breath-by-breath measurements from cardiopulmonary exercise testing and clinical data through a deep learning survival neural network. European Heart Journal - Digital Health. 5(3). 324–334.

Taha, Karim, Heather J. Ross, Mohammad Peikari, et al.. (2020). AN ENSEMBLE-BASED APPROACH TO THE DEVELOPMENT OF CLINICAL PREDICTION MODELS FOR FUTURE-ONSET HEART FAILURE AND CORONARY ARTERY DISEASE USING MACHINE LEARNING. Journal of the American College of Cardiology. 75(11). 2046–2046. 4 indexed citations

Akbar, Shazia, et al.. (2019). Automated and Manual Quantification of Tumour Cellularity in Digital Slides for Tumour Burden Assessment. Scientific Reports. 9(1). 14099–14099. 36 indexed citations

Gangeh, Mehrdad J., Mohammad Peikari, Anne L. Martel, et al.. (2018). Localization and classification of cell nuclei in post-neoadjuvant breast cancer surgical specimen using fully convolutional networks. 9 indexed citations

Peikari, Mohammad, Sherine Salama, Sharon Nofech‐Mozes, & Anne L. Martel. (2018). A Cluster-then-label Semi-supervised Learning Approach for Pathology Image Classification. Scientific Reports. 8(1). 7193–7193. 105 indexed citations

Akbar, Shazia, Anne L. Martel, Mohammad Peikari, Sherine Salama, & Sharon Nofech‐Mozes. (2018). Determining tumor cellularity in digital slides using ResNet. 29–29. 5 indexed citations

Peikari, Mohammad, Sherine Salama, Sharon Nofech‐Mozes, & Anne L. Martel. (2017). Automatic cellularity assessment from post‐treated breast surgical specimens. Cytometry Part A. 91(11). 1078–1087. 23 indexed citations

Peikari, Mohammad & Anne L. Martel. (2016). Automatic cell detection and segmentation from H and E stained pathology slides using colorspace decorrelation stretching. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 9791. 979114–979114. 8 indexed citations

10.

Peikari, Mohammad, Mehrdad J. Gangeh, Judit Zubovits, G. Clarke, & Anne L. Martel. (2015). Triaging Diagnostically Relevant Regions from Pathology Whole Slides of Breast Cancer: A Texture Based Approach. IEEE Transactions on Medical Imaging. 35(1). 307–315. 57 indexed citations

11.

Peikari, Mohammad, et al.. (2011). Effects of Ultrasound Section-Thickness on Brachytherapy Needle Tip Localization Error. Lecture notes in computer science. 14(Pt 1). 299–306. 5 indexed citations

12.

Peikari, Mohammad, et al.. (2011). Characterization of ultrasound elevation beamwidth artifacts for prostate brachytherapy needle insertion. Medical Physics. 39(1). 246–256. 19 indexed citations

13.

Peikari, Mohammad, et al.. (2011). Section-thickness profiling for brachytherapy ultrasound guidance. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 7964. 79640R–79640R. 4 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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