Matahi Moarii

2.0k total citations · 2 hit papers
12 papers, 1.1k citations indexed

About

Matahi Moarii is a scholar working on Molecular Biology, Oncology and Artificial Intelligence. According to data from OpenAlex, Matahi Moarii has authored 12 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Molecular Biology, 4 papers in Oncology and 4 papers in Artificial Intelligence. Recurrent topics in Matahi Moarii's work include AI in cancer detection (4 papers), Radiomics and Machine Learning in Medical Imaging (3 papers) and Epigenetics and DNA Methylation (3 papers). Matahi Moarii is often cited by papers focused on AI in cancer detection (4 papers), Radiomics and Machine Learning in Medical Imaging (3 papers) and Epigenetics and DNA Methylation (3 papers). Matahi Moarii collaborates with scholars based in France, United States and United Kingdom. Matahi Moarii's co-authors include Thomas Clozel, Mikhail Zaslavskiy, Elodie Pronier, Gilles Wainrib, Pierre Courtiol, Meriem Sefta, Fabien Reyal, Jean‐Philippe Vert, Charlie Saillard and Benoît Schmauch and has published in prestigious journals such as Nature Medicine, Nature Communications and Blood.

In The Last Decade

Matahi Moarii

12 papers receiving 1.1k 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.

Deep learning-based classification of mesothelioma improves prediction of patient outcome

2019 314 citations Pierre Courtiol, Charles Maussion et al. Nature Medicine profile →
A deep learning model to predict RNA-Seq expression of tumours from whole slide images

2020 282 citations Benoît Schmauch, Alberto Romagnoni et al. Nature Communications profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Matahi Moarii France	9	434	422	291	251	215	12	1.1k
Elodie Pronier United States	13	434 1.0×	419 1.0×	424 1.5×	216 0.9×	194 0.9×	17	1.2k
Thomas Clozel United States	13	439 1.0×	463 1.1×	332 1.1×	248 1.0×	265 1.2×	18	1.4k
Luiza Moore United Kingdom	15	225 0.5×	208 0.5×	641 2.2×	574 2.3×	220 1.0×	24	1.4k
Paulette Herlin France	17	241 0.6×	205 0.5×	282 1.0×	254 1.0×	400 1.9×	59	1.1k
Panagiota Ravazoula Greece	18	176 0.4×	139 0.3×	239 0.8×	96 0.4×	197 0.9×	68	890
Vincenzo L’Imperio Italy	18	245 0.6×	241 0.6×	245 0.8×	78 0.3×	175 0.8×	103	953
Richard Colling United Kingdom	18	318 0.7×	263 0.6×	124 0.4×	122 0.5×	252 1.2×	47	769
Tarjei S. Hveem Norway	12	265 0.6×	345 0.8×	161 0.6×	211 0.8×	332 1.5×	21	841
Lana X. Garmire United States	10	163 0.4×	184 0.4×	713 2.5×	348 1.4×	101 0.5×	22	1.1k
Dmitrii Bychkov Finland	10	375 0.9×	369 0.9×	192 0.7×	106 0.4×	219 1.0×	19	830

Countries citing papers authored by Matahi Moarii

Since Specialization

Citations

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

Fields of papers citing papers by Matahi Moarii

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Matahi Moarii

This figure shows the co-authorship network connecting the top 25 collaborators of Matahi Moarii. A scholar is included among the top collaborators of Matahi Moarii 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 Matahi Moarii. Matahi Moarii 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:

12 of 12 papers shown

Saillard, Charlie, Benoît Schmauch, Matahi Moarii, et al.. (2020). Predicting Survival After Hepatocellular Carcinoma Resection Using Deep Learning on Histological Slides. Hepatology. 72(6). 2000–2013. 200 indexed citations

Saillard, Charlie, Benoît Schmauch, Matahi Moarii, et al.. (2020). Predicting survival after hepatocellular carcinoma resection using deep-learning on histological slides. Journal of Hepatology. 73. S381–S381. 14 indexed citations

Schmauch, Benoît, Alberto Romagnoni, Elodie Pronier, et al.. (2020). A deep learning model to predict RNA-Seq expression of tumours from whole slide images. Nature Communications. 11(1). 3877–3877. 282 indexed citations breakdown →

Pronier, Elodie, Benoît Schmauch, Alberto Romagnoni, et al.. (2020). Abstract 2105: HE2RNA: A deep learning model for transcriptomic learning from digital pathology. Cancer Research. 80(16_Supplement). 2105–2105. 2 indexed citations

Courtiol, Pierre, Charles Maussion, Matahi Moarii, et al.. (2019). Deep learning-based classification of mesothelioma improves prediction of patient outcome. Nature Medicine. 25(10). 1519–1525. 314 indexed citations breakdown →

Mortera‐Blanco, Teresa, Marios Dimitriou, Petter Woll, et al.. (2017). SF3B1-initiating mutations in MDS-RSs target lymphomyeloid hematopoietic stem cells. Blood. 130(7). 881–890. 47 indexed citations

Moarii, Matahi & Elli Papaemmanuil. (2017). Classification and risk assessment in AML: integrating cytogenetics and molecular profiling. Hematology. 2017(1). 37–44. 44 indexed citations

Hamy, Anne‐Sophie, Hélène Bonsang‐Kitzis, Marick Laé, et al.. (2016). A Stromal Immune Module Correlated with the Response to Neoadjuvant Chemotherapy, Prognosis and Lymphocyte Infiltration in HER2-Positive Breast Carcinoma Is Inversely Correlated with Hormonal Pathways. PLoS ONE. 11(12). e0167397–e0167397. 8 indexed citations

Moarii, Matahi, Valentina Boeva, Jean‐Philippe Vert, & Fabien Reyal. (2015). Changes in correlation between promoter methylation and gene expression in cancer. BMC Genomics. 16(1). 873–873. 115 indexed citations

10.

Bonsang‐Kitzis, Hélène, Benjamin Sadacca, Anne‐Sophie Hamy, et al.. (2015). Biological network-driven gene selection identifies a stromal immune module as a key determinant of triple-negative breast carcinoma prognosis. OncoImmunology. 5(1). e1061176–e1061176. 28 indexed citations

11.

Moarii, Matahi, Fabien Reyal, & Jean‐Philippe Vert. (2015). Integrative DNA methylation and gene expression analysis to assess the universality of the CpG island methylator phenotype. Human Genomics. 9(1). 26–26. 12 indexed citations

12.

Moarii, Matahi, Brigitte Sigal‐Zafrani, Alain Fourquet, et al.. (2014). Epigenomic Alterations in Breast Carcinoma from Primary Tumor to Locoregional Recurrences. PLoS ONE. 9(8). e103986–e103986. 6 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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