Mohammad Yaqub

2.3k citations
50 papers · 865 · 1 hit paper · h-index 15

Impact in

Papers in

Mohammad Yaqub

42 papers receiving 844 citations

Hit Papers

Deep Learning Techniques for Diabetic Retinopathy Classification: A Survey 2022 · 136 citations
1360+1+2Years since publication4080120

Peers

Mohammad Yaqub
Comparison fields: 5 of 110
  • Health Informatics 52
  • Pediatrics, Perinatology and Child Health 266
  • Health Information Management 61
  • Radiology, Nuclear Medicine and Imaging 283
  • Ophthalmology 76
Replace Monica Franzese with:
Monica Franzese Italy
Fajin Dong China
Dongdong Zhang China
Suresh Seshadri India
Jianan Chen China
Mahmudul Hasan Bangladesh
Wen‐Bin Zou China
Yuancheng Wang China
Liangliang Liu China
Mats Holmström Sweden
Mohammad Yaqub relative to Monica Franzese Italy Monica Franzese's profile →
Citations per field
00.5×10×12.7×
Monica Franzese · 1×
Citations per year

Countries citing papers authored by Mohammad Yaqub

Since Specialization
Citations

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

Fields of papers citing papers by Mohammad Yaqub

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Mohammad Yaqub, 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 Mohammad Yaqub Line = papers co-authored together Mohammad Yaqub links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 50 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Deep Learning Techniques for Diabetic Retinopathy Classification: A Survey
Hit paper breakdown →
2022136
2 202077
3 201875
4 201269
5 201567
6 201857
7 201752
8 201342
9 201930
10 201724
11 198024
12 202020
13 201820
14 201219
15 202316
16 202114
17 201513
18 202011
19 202110
20 20148

About Mohammad Yaqub

Mohammad Yaqub is a scholar working on Artificial Intelligence, Pediatrics, Perinatology and Child Health, Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging and Molecular Biology, having authored 50 papers that have together received 865 indexed citations. Recurring topics across this work include Fetal and Pediatric Neurological Disorders (14 papers), Domain Adaptation and Few-Shot Learning (10 papers), Neonatal and fetal brain pathology (6 papers), AI in cancer detection (6 papers), Prenatal Screening and Diagnostics (5 papers), Cleft Lip and Palate Research (4 papers), Brain Tumor Detection and Classification (4 papers) and Artificial Intelligence in Healthcare and Education (3 papers). The work is most often cited by research in Health Informatics (52 citations), Pediatrics, Perinatology and Child Health (266 citations), Health Information Management (61 citations), Radiology, Nuclear Medicine and Imaging (283 citations) and Ophthalmology (76 citations). Mohammad Yaqub has collaborated with scholars based in United Kingdom, United Arab Emirates and United States. Frequent co-authors include J. Alison Noble, Aris T. Papageorghiou, Ana I. L. Namburete, M K Javaid, Maha Saadeh, Hazem Hiary, Heba Saadeh, Cyrus Cooper, Brenda Kelly and B. Kemp. Their work appears in journals such as Ultrasound in Obstetrics and Gynecology, Ultrasound in Medicine & Biology, Medical Image Analysis, Scientific Reports and IEEE Access.

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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