Tanveer Fathima Syeda-Mahmood
Tanveer Fathima Syeda-Mahmood publishes mostly in Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging and Artificial Intelligence, on topics such as Medical Image Segmentation Techniques, Image Retrieval and Classification Techniques and Radiomics and Machine Learning in Medical Imaging.
- World rank
- #1,389,511 of 7,710,434 ranked researchers
- Rank in United States
- #439,172 of 1,627,098
- Works
- 233
- Citations
- 4.9k
- Citations per work
- 21.0
What does Tanveer Fathima Syeda-Mahmood research?
Tanveer Fathima Syeda-Mahmood's work is mostly in Computer Science (48%), Medicine (20%), Biochemistry, Genetics and Molecular Biology (6%).
Their six largest subfields, inside their fields and domains; the grey slice is everything else they publish. The interactive view splits every one of their works down to single topics.
The fields and subfields, with their numbers
- Physical Sciences11951.0%
- Computer Science11147.8%
- Engineering73.2%
- Everything else5322.6%
- Health Sciences4820.4%
- Medicine4820.4%
- Life Sciences146.0%
- 1Computer Vision and Pattern Recognition30% of their works
- 2Radiology, Nuclear Medicine and Imaging18% of their works
- 3Artificial Intelligence17% of their works
- 4Molecular Biology6% of their works
- 5Biomedical Engineering3% of their works
- 6Cardiology and Cardiovascular Medicine3% of their works
Research topics
Which keywords describe Tanveer Fathima Syeda-Mahmood's research?
The keywords of their largest research topics: Deep Learning, Machine Learning, Texture Analysis, Medical Image Analysis, Medical Imaging, Convolutional Neural Networks, Graph Cuts and Image Segmentation.
- Video Summarization
- Text Mining
- Local Descriptors
- Chest X-Ray
- Histopathology Images
- Radiomics
- Shape Matching
- Image Segmentation
- Convolutional Neural Networks
- Medical Image Analysis
- Machine Learning
- Deep Learning
- Texture Analysis
- Medical Imaging
- Graph Cuts
- Content-Based Image Retrieval
- Quantitative Analysis
- Computer-Aided Detection
- COVID-19
- Feature Matching
- Biomedical Ontologies
- Content-Based Retrieval
Size is their works in the topics tagged with each word, from their 8 largest topics. Each links to the topic it comes from most. The words come from the keyword list OpenAlex gives each topic, not from the text of the papers, so a word can appear that none of the papers uses.
All 22 words, with their numbers
- Deep Learning1444 topics
- Machine Learning1173 topics
- Texture Analysis862 topics
- Medical Image Analysis822 topics
- Medical Imaging712 topics
- Convolutional Neural Networks672 topics
- Graph Cuts471 topic
- Image Segmentation471 topic
- Content-Based Image Retrieval431 topic
- Shape Matching431 topic
- Quantitative Analysis391 topic
- Radiomics391 topic
- Computer-Aided Detection351 topic
- Histopathology Images351 topic
- COVID-19321 topic
- Chest X-Ray321 topic
- Feature Matching301 topic
- Local Descriptors301 topic
- Biomedical Ontologies211 topic
- Text Mining211 topic
- Content-Based Retrieval171 topic
- Video Summarization171 topic
Where does Tanveer Fathima Syeda-Mahmood work?
Tanveer Fathima Syeda-Mahmood's main affiliation in the publication record is IBM Research - Almaden, United States.
How many publications and citations does Tanveer Fathima Syeda-Mahmood have?
OpenAlex counts 233 works and 4,897 citations for Tanveer Fathima Syeda-Mahmood, an h-index of 31, ranking #1,389,511 of 7,710,434 researchers worldwide on the quality score.
Ranked on field-normalised citation excellence (50%), output (30%) and citations (20%). Counts come from OpenAlex author records, which occasionally merge different people who share a name or split one person into several.
Papers, co-authors, who cited this work and researchers on the nearest topics have tabs of their own, above. Is this your page? Claim it with your ORCID iD, or request a correction or removal.
Discussion
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