William Weiser

12 papers receiving 398 citations

Peers

William Weiser
Comparison fields: 5 of 114
  • Hematology 55
  • Pulmonary and Respiratory Medicine 120
  • Radiology, Nuclear Medicine and Imaging 67
  • Artificial Intelligence 87
  • Computer Vision and Pattern Recognition 52
Replace Andreas O. H. Gerstner with:
Andreas O. H. Gerstner Germany
Murat Borlu Türkiye
Gordana Basta-Jovanović Serbia
L. R. Jarvis Australia
Kaori Abe Japan
Jolanta E. Kunicka United States
Giu‐Cheng Hsu Taiwan
Dominique Touchard France
Yongjing Cheng China
Boris Oskotsky United States
William Weiser relative to Andreas O. H. Gerstner Germany Andreas O. H. Gerstner's profile →
Citations per field
00.5×2.8×
Andreas O. H. Gerstner · 1×
Citations per year

Countries citing papers authored by William Weiser

Since Specialization
Citations

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

Fields of papers citing papers by William Weiser

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside William Weiser, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with William Weiser Line = papers co-authored together William Weiser links everyone, so they are left out of the graph.

All Works

12 of 12 papers shown
#Work
1 1990179
2 1965133
3 196326
4 199125
5 198923
6 201221
7 199214
8 20047
9 20185
10 19895
11 19924
12 20213

About William Weiser

William Weiser is a scholar working on Molecular Biology, Pulmonary and Respiratory Medicine, Epidemiology, Artificial Intelligence and Immunology and Allergy, having authored 12 papers that have together received 445 indexed citations. Recurring topics across this work include Cell Adhesion Molecules Research (2 papers), AI in cancer detection (2 papers), SARS-CoV-2 and COVID-19 Research (1 paper), Chronic Myeloid Leukemia Treatments (1 paper), Protein purification and stability (1 paper), Osteoarthritis Treatment and Mechanisms (1 paper), Disaster Response and Management (1 paper) and Toxin Mechanisms and Immunotoxins (1 paper). The work is most often cited by research in Hematology (55 citations), Pulmonary and Respiratory Medicine (120 citations), Radiology, Nuclear Medicine and Imaging (67 citations), Artificial Intelligence (87 citations) and Computer Vision and Pattern Recognition (52 citations). William Weiser has collaborated with scholars based in Canada, United States and United Kingdom. Frequent co-authors include Henry Z. Movat, James F. Mustard, Michael Glynn, Curtis B. Caldwell, Roberta A. Jong, David W. Holdsworth, G Cooke, V. Hoffstein, Richard L. Haney and Neil V.P. Fernando. Their work appears in journals such as CHEST Journal, American Journal of Roentgenology, Physics in Medicine and Biology, The Journal of Cell Biology and The Journal of Experimental Medicine.

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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