Nabila Abraham

1.2k total citations · 1 hit paper
5 papers, 692 citations indexed

About

Nabila Abraham is a scholar working on Artificial Intelligence, Radiology, Nuclear Medicine and Imaging and Neurology. According to data from OpenAlex, Nabila Abraham has authored 5 papers receiving a total of 692 indexed citations (citations by other indexed papers that have themselves been cited), including 3 papers in Artificial Intelligence, 2 papers in Radiology, Nuclear Medicine and Imaging and 2 papers in Neurology. Recurrent topics in Nabila Abraham's work include Radiomics and Machine Learning in Medical Imaging (2 papers), Medical Imaging and Analysis (2 papers) and Machine Learning in Healthcare (2 papers). Nabila Abraham is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (2 papers), Medical Imaging and Analysis (2 papers) and Machine Learning in Healthcare (2 papers). Nabila Abraham collaborates with scholars based in Canada and France. Nabila Abraham's co-authors include Naimul Khan, Marcia Hon, Farzad Khalvati, D. Androutsos, Laurent Milot, Dominik Deniffel, Khashayar Namdar, Masoom A. Haider, Xin Dong and McCullen Sandora and has published in prestigious journals such as IEEE Access and European Radiology.

In The Last Decade

Nabila Abraham

5 papers receiving 674 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.

A Novel Focal Tversky Loss Function With Improved Attention U-Net for Lesion Segmentation

2019 527 citations Nabila Abraham, Naimul Khan profile →

Peers

Nabila Abraham

AI

CVPR

RNMI

NEURO

BE

Tao Song China

Ehsan Khodapanah Aghdam Germany

Dominik Müller Germany

Moein Heidari Iran

Phillip Chlap Australia

Yan Chai Hum Malaysia

Liangliang Liu China

Shekoofeh Azizi United States

Patricio Rivera Chile

Tao Song China

Nabila Abraham

250 ×0.9

AI

315 ×1.2

CVPR

328 ×1.4

RNMI

142 ×1.0

NEURO

120 ×1.1

BE

Citations per year, relative to Nabila Abraham Nabila Abraham (= 1×) peers Tao Song

Countries citing papers authored by Nabila Abraham

Since Specialization

Citations

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

Fields of papers citing papers by Nabila Abraham

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Nabila Abraham

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

All Works

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5 of 5 papers shown

1.

Sandora, McCullen, et al.. (2022). Explaining the Effectiveness of Multi-Task Learning for Efficient Knowledge Extraction from Spine MRI Reports. 130–140. 2 indexed citations

2.

Deniffel, Dominik, Nabila Abraham, Khashayar Namdar, et al.. (2020). Using decision curve analysis to benchmark performance of a magnetic resonance imaging–based deep learning model for prostate cancer risk assessment. European Radiology. 30(12). 6867–6876. 25 indexed citations

3.

Khan, Naimul, Nabila Abraham, & Marcia Hon. (2019). Transfer Learning With Intelligent Training Data Selection for Prediction of Alzheimer’s Disease. IEEE Access. 7. 72726–72735. 126 indexed citations

4.

Abraham, Nabila & Naimul Khan. (2019). A Novel Focal Tversky Loss Function With Improved Attention U-Net for Lesion Segmentation. 683–687. 527 indexed citations breakdown →

5.

Abraham, Nabila, et al.. (2019). Deep Learning for Semantic Segmentation of Brachial Plexus Nervesin Ultrasound Images Using U-Net and M-Net. 12 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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