Fayyaz Minhas

2.8k total citations
72 papers, 1.4k citations indexed

About

Fayyaz Minhas is a scholar working on Artificial Intelligence, Molecular Biology and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Fayyaz Minhas has authored 72 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 39 papers in Artificial Intelligence, 26 papers in Molecular Biology and 19 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Fayyaz Minhas's work include AI in cancer detection (33 papers), Radiomics and Machine Learning in Medical Imaging (17 papers) and Machine Learning in Bioinformatics (11 papers). Fayyaz Minhas is often cited by papers focused on AI in cancer detection (33 papers), Radiomics and Machine Learning in Medical Imaging (17 papers) and Machine Learning in Bioinformatics (11 papers). Fayyaz Minhas collaborates with scholars based in United Kingdom, Pakistan and United States. Fayyaz Minhas's co-authors include Nasir Rajpoot, Amina Asif, Asa Ben‐Hur, Simon Graham, Muhammad Arif, Shan E Ahmed Raza, David Snead, Mohsin Bilal, Wajid Arshad Abbasi and Wenqi Lu and has published in prestigious journals such as Nucleic Acids Research, SHILAP Revista de lepidopterología and Bioinformatics.

In The Last Decade

Fayyaz Minhas

69 papers receiving 1.4k citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Fayyaz Minhas United Kingdom	21	536	507	419	186	162	72	1.4k
John H. Phan United States	21	465 0.9×	712 1.4×	255 0.6×	257 1.4×	90 0.6×	68	1.7k
Tim Becker Germany	15	372 0.7×	913 1.8×	173 0.4×	365 2.0×	170 1.0×	33	2.4k
Dongxiao Zhu United States	22	353 0.7×	1.2k 2.4×	237 0.6×	64 0.3×	126 0.8×	101	2.1k
Ming Fan China	21	470 0.9×	381 0.8×	934 2.2×	95 0.5×	123 0.8×	79	1.6k
Bahram Parvin United States	24	533 1.0×	586 1.2×	346 0.8×	500 2.7×	359 2.2×	84	1.8k
Mikhail Zaslavskiy France	10	578 1.1×	302 0.6×	433 1.0×	271 1.5×	173 1.1×	17	1.3k
Nicolas Coudray United States	17	1.2k 2.2×	554 1.1×	1.1k 2.6×	258 1.4×	495 3.1×	49	2.5k
Maxwell W. Libbrecht Canada	12	280 0.5×	905 1.8×	101 0.2×	47 0.3×	34 0.2×	29	1.7k
Pegah Khosravi United States	14	439 0.8×	316 0.6×	398 0.9×	102 0.5×	95 0.6×	25	1.3k
Valentina L. Kouznetsova United States	21	155 0.3×	529 1.0×	1.9k 4.5×	1.3k 7.1×	251 1.5×	84	3.1k

Countries citing papers authored by Fayyaz Minhas

Since Specialization

Citations

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

Fields of papers citing papers by Fayyaz Minhas

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Fayyaz Minhas

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

20 of 20 papers shown

Wright, George, et al.. (2025). Automatic discovery of robust risk groups from limited survival data across biomedical modalities. Machine Learning with Applications. 23. 100814–100814.

Lashen, Ayat, Noorul Wahab, Michael S. Toss, et al.. (2024). Characterization of Breast Cancer Intra-Tumor Heterogeneity Using Artificial Intelligence. Cancers. 16(22). 3849–3849. 1 indexed citations

Minhas, Fayyaz, et al.. (2024). Synthesis of annotated colon cancer tissue images from gland layout. 15–15. 1 indexed citations

Evans, Harriet, et al.. (2024). Large multimodal model‐based standardisation of pathology reports with confidence and its prognostic significance. The Journal of Pathology Clinical Research. 10(6). e70010–e70010. 3 indexed citations

Şahin, Mehmet, Benjamin C. B. Symons, Pushpak Pati, et al.. (2024). Efficient Parameter Optimisation for Quantum Kernel Alignment: A Sub-sampling Approach in Variational Training. Quantum. 8. 1502–1502. 4 indexed citations

Jahanifar, Mostafa, Lawrence S. Young, Asa Ben‐Hur, et al.. (2023). Cross-linking breast tumor transcriptomic states and tissue histology. Cell Reports Medicine. 4(12). 101313–101313. 2 indexed citations

Wahab, Noorul, Michael S. Toss, Asmaa Ibrahim, et al.. (2023). Evaluation of tumour infiltrating lymphocytes in luminal breast cancer using artificial intelligence. British Journal of Cancer. 129(11). 1747–1758. 22 indexed citations

Ibrahim, Asmaa, Mostafa Jahanifar, Noorul Wahab, et al.. (2023). Artificial Intelligence-Based Mitosis Scoring in Breast Cancer: Clinical Application. Modern Pathology. 37(3). 100416–100416. 11 indexed citations

Evans, Harriet, Fayyaz Minhas, Noorul Wahab, et al.. (2023). Standardized Clinical Annotation of Digital Histopathology Slides at the Point of Diagnosis. Modern Pathology. 36(11). 100297–100297. 4 indexed citations

10.

Dawood, Muhammad, et al.. (2023). SynCLay: Interactive synthesis of histology images from bespoke cellular layouts. Medical Image Analysis. 91. 102995–102995. 8 indexed citations

11.

Wahab, Noorul, Michael S. Toss, Asmaa Ibrahim, et al.. (2023). Deciphering the Morphology of Tumor-Stromal Features in Invasive Breast Cancer Using Artificial Intelligence. Modern Pathology. 36(10). 100254–100254. 5 indexed citations

12.

Graham, Simon, Quoc Dang Vu, Mostafa Jahanifar, et al.. (2022). TIAToolbox as an end-to-end library for advanced tissue image analytics. SHILAP Revista de lepidopterología. 2(1). 120–120. 52 indexed citations

13.

Minhas, Fayyaz, et al.. (2022). On the choice of negative examples for prediction of host-pathogen protein interactions. SHILAP Revista de lepidopterología. 2. 1083292–1083292.

14.

Awan, Ruqayya, Ayesha Azam, Muhammad Shaban, et al.. (2021). Deep learning based digital cell profiles for risk stratification of urine cytology images. Cytometry Part A. 99(7). 732–742. 31 indexed citations

15.

Jarvis, Stephen A., et al.. (2021). Elementary effects analysis of factors controlling COVID-19 infections in computational simulation reveals the importance of social distancing and mask usage. Computers in Biology and Medicine. 134. 104369–104369. 19 indexed citations

16.

Asif, Amina, Kyle E. Watters, Anthony T. Iavarone, et al.. (2020). Machine learning predicts new anti-CRISPR proteins. Nucleic Acids Research. 48(9). 4698–4708. 75 indexed citations

17.

Huang, Le, Haidong Yi, Amina Asif, et al.. (2020). AcrDB: a database of anti-CRISPR operons in prokaryotes and viruses. Nucleic Acids Research. 49(D1). D622–D629. 38 indexed citations

18.

Minhas, Fayyaz, et al.. (2019). AMAP: Hierarchical multi-label prediction of biologically active and antimicrobial peptides. Computers in Biology and Medicine. 107. 172–181. 62 indexed citations

19.

Asif, Amina, et al.. (2018). A generalized meta-loss function for distillation and learning using privileged information for classification and regression. arXiv (Cornell University). 1 indexed citations

20.

Minhas, Fayyaz & Muhammad Arif. (2008). Robust electrocardiogram (ECG) beat classification using discrete wavelet transform. Physiological Measurement. 29(5). 555–570. 74 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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