Hurvitz Ai

23 papers and 367 indexed citations i.

About

Hurvitz Ai is a scholar working on Hematology, Molecular Biology and Immunology. According to data from OpenAlex, Hurvitz Ai has authored 23 papers receiving a total of 367 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Hematology, 5 papers in Molecular Biology and 4 papers in Immunology. Recurrent topics in Hurvitz Ai’s work include Glycosylation and Glycoproteins Research (5 papers), Blood groups and transfusion (4 papers) and Multiple Myeloma Research and Treatments (4 papers). Hurvitz Ai is often cited by papers focused on Glycosylation and Glycoproteins Research (5 papers), Blood groups and transfusion (4 papers) and Multiple Myeloma Research and Treatments (4 papers). Hurvitz Ai collaborates with scholars based in and . Hurvitz Ai's co-authors include Matus Re, MacEwen Eg, Leifer Ce, Stuart D. Saal, Kay Wj, Saood Murad, Good Ra, Scott Moroff and Stenzel Kh and has published in prestigious journals such as PubMed.

In The Last Decade

Co-authorship network of co-authors of Hurvitz Ai i

Fields of papers citing papers by Hurvitz Ai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries citing papers authored by Hurvitz Ai

Since Specialization
Citations

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

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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2025