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Isaac Shiri

D-Index & Metrics

Discipline name D-Index World Ranking Current World Ranking National Ranking Current National Ranking Publications Citations
Computer Science 37 10941 10635 546 533 72 3750

Isaac Shiri publications per year

The chart shows the history of publications by Isaac Shiri between 1998 and 2026, highlighting the no. of papers published in each year and offering an overview of the publication velocity of this scholar. Isaac Shiri published across 29 years, from 1998 to 2026, averaging 8.3 papers a year. Output peaked at 48 publications in 2022. 32 of the 242 publications appeared in the last two years.

No. of publications
10 20 30 40
Bar chart. Horizontal axis: year, 1998 to 2026. Vertical axis: number of publications, 0 to 48. Peak 48 publications in 2022. 1998: 1 publication 1999: 0 publications 2000: 0 publications 2001: 0 publications 2002: 0 publications 2003: 0 publications 2004: 0 publications 2005: 0 publications 2006: 0 publications 2007: 0 publications 2008: 0 publications 2009: 0 publications 2010: 0 publications 2011: 0 publications 2012: 0 publications 2013: 0 publications 2014: 0 publications 2015: 1 publication 2016: 1 publication 2017: 3 publications 2018: 7 publications 2019: 19 publications 2020: 23 publications 2021: 25 publications 2022: 48 publications 2023: 41 publications 2024: 41 publications 2025: 29 publications 2026: 3 publications
1998 2026

242 publications in total across all disciplines

View publications per year as a table
Isaac Shiri: publications per year, 1998 to 2026
Year Publications
1998 1
1999 0
2000 0
2001 0
2002 0
2003 0
2004 0
2005 0
2006 0
2007 0
2008 0
2009 0
2010 0
2011 0
2012 0
2013 0
2014 0
2015 1
2016 1
2017 3
2018 7
2019 19
2020 23
2021 25
2022 48
2023 41
2024 41
2025 29
2026 3
Total 242
Download as CSV

Isaac Shiri publication distribution in Computer Science in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Computer Science in 2026. The highlighted bar marks where Isaac Shiri sits on this spectrum.

No. of scientists
200 400 600
Bar chart with 97 bars. Horizontal axis: publications, 32–41 to 991+. Vertical axis: number of scientists, 0 to 609. Most scientists, 609, have 142–151 publications. The last bar groups every scientist with 991 publications or more. The highlighted bar, 72–81 publications, is where this scientist sits. 32–41 publications: 7 scientists 42–51 publications: 22 scientists 52–61 publications: 82 scientists 62–71 publications: 134 scientists 72–81 publications: 249 scientists 82–91 publications: 324 scientists 92–101 publications: 421 scientists 102–111 publications: 420 scientists 112–121 publications: 497 scientists 122–131 publications: 544 scientists 132–141 publications: 555 scientists 142–151 publications: 609 scientists 152–161 publications: 559 scientists 162–171 publications: 534 scientists 172–181 publications: 556 scientists 182–191 publications: 583 scientists 192–201 publications: 519 scientists 202–211 publications: 508 scientists 212–221 publications: 490 scientists 222–231 publications: 437 scientists 232–241 publications: 423 scientists 242–251 publications: 408 scientists 252–261 publications: 377 scientists 262–271 publications: 301 scientists 272–281 publications: 335 scientists 282–291 publications: 320 scientists 292–301 publications: 293 scientists 302–311 publications: 250 scientists 312–321 publications: 238 scientists 322–331 publications: 206 scientists 332–341 publications: 209 scientists 342–351 publications: 208 scientists 352–361 publications: 162 scientists 362–371 publications: 176 scientists 372–381 publications: 127 scientists 382–391 publications: 158 scientists 392–401 publications: 128 scientists 402–411 publications: 104 scientists 412–421 publications: 94 scientists 422–431 publications: 99 scientists 432–441 publications: 83 scientists 442–451 publications: 108 scientists 452–461 publications: 73 scientists 462–471 publications: 77 scientists 472–481 publications: 69 scientists 482–491 publications: 84 scientists 492–501 publications: 62 scientists 502–511 publications: 54 scientists 512–521 publications: 57 scientists 522–531 publications: 51 scientists 532–541 publications: 51 scientists 542–551 publications: 32 scientists 552–561 publications: 38 scientists 562–571 publications: 28 scientists 572–581 publications: 43 scientists 582–591 publications: 33 scientists 592–601 publications: 41 scientists 602–611 publications: 32 scientists 612–621 publications: 28 scientists 622–631 publications: 25 scientists 632–641 publications: 27 scientists 642–651 publications: 17 scientists 652–661 publications: 20 scientists 662–671 publications: 17 scientists 672–681 publications: 15 scientists 682–691 publications: 14 scientists 692–701 publications: 21 scientists 702–711 publications: 13 scientists 712–721 publications: 12 scientists 722–731 publications: 19 scientists 732–741 publications: 14 scientists 742–751 publications: 12 scientists 752–761 publications: 10 scientists 762–771 publications: 10 scientists 772–781 publications: 11 scientists 782–791 publications: 10 scientists 792–801 publications: 11 scientists 802–811 publications: 8 scientists 812–821 publications: 8 scientists 822–831 publications: 7 scientists 832–841 publications: 11 scientists 842–851 publications: 10 scientists 852–861 publications: 5 scientists 862–871 publications: 9 scientists 872–881 publications: 4 scientists 882–891 publications: 6 scientists 892–901 publications: 3 scientists 902–911 publications: 6 scientists 912–921 publications: 3 scientists 922–931 publications: 2 scientists 932–941 publications: 2 scientists 942–951 publications: 2 scientists 952–961 publications: 3 scientists 962–971 publications: 3 scientists 972–981 publications: 3 scientists 982–990 publications: 5 scientists 991+ publications: 100 scientists
32–41 publications 991+

This scientist: 72 publications — 2nd percentile

2% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 991 publications or more.

View publications distribution as a table
Number of Computer Science scientists by publication count, Research.com 2026 ranking edition. Based on 14,188 ranked scientists.
Publications Scientists This scientist
32–41 7
42–51 22
52–61 82
62–71 134
72–81 249 72
82–91 324
92–101 421
102–111 420
112–121 497
122–131 544
132–141 555
142–151 609
152–161 559
162–171 534
172–181 556
182–191 583
192–201 519
202–211 508
212–221 490
222–231 437
232–241 423
242–251 408
252–261 377
262–271 301
272–281 335
282–291 320
292–301 293
302–311 250
312–321 238
322–331 206
332–341 209
342–351 208
352–361 162
362–371 176
372–381 127
382–391 158
392–401 128
402–411 104
412–421 94
422–431 99
432–441 83
442–451 108
452–461 73
462–471 77
472–481 69
482–491 84
492–501 62
502–511 54
512–521 57
522–531 51
532–541 51
542–551 32
552–561 38
562–571 28
572–581 43
582–591 33
592–601 41
602–611 32
612–621 28
622–631 25
632–641 27
642–651 17
652–661 20
662–671 17
672–681 15
682–691 14
692–701 21
702–711 13
712–721 12
722–731 19
732–741 14
742–751 12
752–761 10
762–771 10
772–781 11
782–791 10
792–801 11
802–811 8
812–821 8
822–831 7
832–841 11
842–851 10
852–861 5
862–871 9
872–881 4
882–891 6
892–901 3
902–911 6
912–921 3
922–931 2
932–941 2
942–951 2
952–961 3
962–971 3
972–981 3
982–990 5
991+ 100
Download as CSV

Isaac Shiri D-index placement in Computer Science in 2026

The chart shows the D-index (discipline H-index) distribution of Computer Science scientists ranked by Research.com in 2026. The highlighted bar marks where Isaac Shiri sits on this spectrum.

No. of scientists
200 400 600 800
Bar chart with 52 bars. Horizontal axis: D-Index, 30–31 to 131+. Vertical axis: number of scientists, 0 to 990. Most scientists, 990, have 36–37 D-Index. The last bar groups every scientist with 131 D-Index or more. The highlighted bar, 36–37 D-Index, is where this scientist sits. 30–31 D-Index: 879 scientists 32–33 D-Index: 983 scientists 34–35 D-Index: 918 scientists 36–37 D-Index: 990 scientists 38–39 D-Index: 968 scientists 40–41 D-Index: 907 scientists 42–43 D-Index: 821 scientists 44–45 D-Index: 763 scientists 46–47 D-Index: 689 scientists 48–49 D-Index: 543 scientists 50–51 D-Index: 543 scientists 52–53 D-Index: 518 scientists 54–55 D-Index: 500 scientists 56–57 D-Index: 458 scientists 58–59 D-Index: 400 scientists 60–61 D-Index: 337 scientists 62–63 D-Index: 308 scientists 64–65 D-Index: 292 scientists 66–67 D-Index: 249 scientists 68–69 D-Index: 213 scientists 70–71 D-Index: 192 scientists 72–73 D-Index: 189 scientists 74–75 D-Index: 165 scientists 76–77 D-Index: 139 scientists 78–79 D-Index: 119 scientists 80–81 D-Index: 121 scientists 82–83 D-Index: 113 scientists 84–85 D-Index: 88 scientists 86–87 D-Index: 87 scientists 88–89 D-Index: 75 scientists 90–91 D-Index: 69 scientists 92–93 D-Index: 57 scientists 94–95 D-Index: 46 scientists 96–97 D-Index: 38 scientists 98–99 D-Index: 34 scientists 100–101 D-Index: 36 scientists 102–103 D-Index: 27 scientists 104–105 D-Index: 37 scientists 106–107 D-Index: 18 scientists 108–109 D-Index: 31 scientists 110–111 D-Index: 19 scientists 112–113 D-Index: 16 scientists 114–115 D-Index: 12 scientists 116–117 D-Index: 20 scientists 118–119 D-Index: 15 scientists 120–121 D-Index: 5 scientists 122–123 D-Index: 20 scientists 124–125 D-Index: 8 scientists 126–127 D-Index: 5 scientists 128–129 D-Index: 7 scientists 130 D-Index: 3 scientists 131+ D-Index: 98 scientists
30–31 D-Index 131+

This scientist: 37 D-Index — 27th percentile

27% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 131 D-Index or more.

View D-Index distribution as a table
Number of Computer Science scientists by D-index, Research.com 2026 ranking edition. Based on 14,188 ranked scientists.
D-Index Scientists This scientist
30–31 879
32–33 983
34–35 918
36–37 990 37
38–39 968
40–41 907
42–43 821
44–45 763
46–47 689
48–49 543
50–51 543
52–53 518
54–55 500
56–57 458
58–59 400
60–61 337
62–63 308
64–65 292
66–67 249
68–69 213
70–71 192
72–73 189
74–75 165
76–77 139
78–79 119
80–81 121
82–83 113
84–85 88
86–87 87
88–89 75
90–91 69
92–93 57
94–95 46
96–97 38
98–99 34
100–101 36
102–103 27
104–105 37
106–107 18
108–109 31
110–111 19
112–113 16
114–115 12
116–117 20
118–119 15
120–121 5
122–123 20
124–125 8
126–127 5
128–129 7
130 3
131+ 98
Download as CSV

Overview

Isaac Shiri is affiliated with University Hospital Bern in Germany and has made contributions primarily in the field of Medicine, with a particular focus on Radiology, Nuclear Medicine, and Imaging.

Their research encompasses several subfields including Biomedical Engineering, Pulmonary and Respiratory Medicine, Cardiology and Cardiovascular Medicine, and Artificial Intelligence. The scientist's work covers multiple main topics, notably:

  • Radiomics and Machine Learning in Medical Imaging
  • Advanced X-ray and CT Imaging
  • Medical Imaging Techniques and Applications
  • Lung Cancer Diagnosis and Treatment
  • COVID-19 diagnosis using AI
  • Cardiac Imaging and Diagnostics
  • AI in cancer detection

The most frequent publication venues where their research appears include:

  • 2021 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC)
  • European Journal of Nuclear Medicine and Molecular Imaging
  • bioRxiv (Cold Spring Harbor Laboratory)
  • Computers in Biology and Medicine
  • European Heart Journal

Frequent collaborators in their research include Habib Zaidi, Ghasem Hajianfar, Yazdan Salimi, Hossein Arabi, and Arman Rahmim.

Selected recent papers authored or coauthored by Isaac Shiri are:

  • Next-Generation Radiogenomics Sequencing for Prediction of EGFR and KRAS Mutation Status in NSCLC Patients Using Multimodal Imaging and Machine Learning Algorithms, 2020, Molecular Imaging and Biology
  • The promise of artificial intelligence and deep learning in PET and SPECT imaging, 2021, Physica Medica
  • Deep learning-assisted ultra-fast/low-dose whole-body PET/CT imaging, 2021, European Journal of Nuclear Medicine and Molecular Imaging
  • The Image Biomarker Standardization Initiative: Standardized Convolutional Filters for Reproducible Radiomics and Enhanced Clinical Insights, 2024, Radiology
  • Radiomics for classification of bone mineral loss: A machine learning study, 2020, Diagnostic and Interventional Imaging

Best Publications

  • The impact of image reconstruction settings on 18F-FDG PET radiomic features: multi-scanner phantom and patient studies.

    Isaac Shiri;Arman Rahmim;Pardis Ghaffarian;Parham Geramifar

  • The promise of artificial intelligence and deep learning in PET and SPECT imaging.

    Hossein Arabi;Azadeh AkhavanAllaf;Amirhossein Sanaat;Isaac Shiri

  • MFP-Unet: A novel deep learning based approach for left ventricle segmentation in echocardiography

    Shakiba Moradi;Mostafa Ghelich Oghli;Azin Alizadehasl;Isaac Shiri

  • Next Generation Radiogenomics Sequencing for Prediction of EGFR and KRAS Mutation Status in NSCLC Patients Using Multimodal Imaging and Machine Learning Approaches

    Isaac Shiri;Hassan Maleki;Ghasem Hajianfar;Hamid Abdollahi

  • Radiomics for classification of bone mineral loss: A machine learning study

    S. Rastegar;M. Vaziri;Y. Qasempour;M.R. Akhash

  • Machine learning-based radiomic models to predict intensity-modulated radiation therapy response, Gleason score and stage in prostate cancer

    Hamid Abdollahi;Bahram Mofid;Isaac Shiri;Isaac Shiri;Abolfazl Razzaghdoust

  • Machine learning-based prognostic modeling using clinical data and quantitative radiomic features from chest CT images in COVID-19 patients.

    Isaac Shiri;Majid Sorouri;Parham Geramifar;Mostafa Nazari

  • Noninvasive Fuhrman grading of clear cell renal cell carcinoma using computed tomography radiomic features and machine learning

    Mostafa Nazari;Isaac Shiri;Ghasem Hajianfar;Niki Oveisi

  • Radiomics-based machine learning model to predict risk of death within 5-years in clear cell renal cell carcinoma patients

    Mostafa Nazari;Isaac Shiri;Habib Zaidi;Habib Zaidi

  • Cochlea CT radiomics predicts chemoradiotherapy induced sensorineural hearing loss in head and neck cancer patients: A machine learning and multi-variable modelling study

    Hamid Abdollahi;Shayan Mostafaei;Susan Cheraghi;Isaac Shiri

  • Direct attenuation correction of brain PET images using only emission data via a deep convolutional encoder-decoder (Deep-DAC)

    Isaac Shiri;Pardis Ghafarian;Parham Geramifar;Kevin Ho-Yin Leung

  • Deep learning-based auto-segmentation of organs at risk in high-dose rate brachytherapy of cervical cancer.

    Reza Mohammadi;Iman Shokatian;Mohammad Salehi;Hossein Arabi

  • Ultra-low-dose chest CT imaging of COVID-19 patients using a deep residual neural network

    Isaac Shiri;Azadeh Akhavanallaf;Amirhossein Sanaat;Yazdan Salimi

  • Non-small cell lung carcinoma histopathological subtype phenotyping using high-dimensional multinomial multiclass CT radiomics signature

    Zahra Khodabakhshi;Shayan Mostafaei;Hossein Arabi;Mehrdad Oveisi

  • Standard SPECT myocardial perfusion estimation from half-time acquisitions using deep convolutional residual neural networks

    Isaac Shiri;Kiarash AmirMozafari Sabet;Hossein Arabi;Mozhgan Pourkeshavarz;Mozhgan Pourkeshavarz

  • CT imaging markers to improve radiation toxicity prediction in prostate cancer radiotherapy by stacking regression algorithm

    Shayan Mostafaei;Shayan Mostafaei;Hamid Abdollahi;Shiva Kazempour Dehkordi;Isaac Shiri

  • Noninvasive O6 Methylguanine-DNA Methyltransferase Status Prediction in Glioblastoma Multiforme Cancer Using Magnetic Resonance Imaging Radiomics Features: Univariate and Multivariate Radiogenomics Analysis

    Ghasem Hajianfar;Isaac Shiri;Hassan Maleki;Niki Oveisi

  • Artificial intelligence-driven assessment of radiological images for COVID-19.

    Yassine Bouchareb;Pegah Moradi Khaniabadi;Faiza Al Kindi;Humoud Al Dhuhli

  • Repeatability of radiomic features in magnetic resonance imaging of glioblastoma: Test─retest and image registration analyses

    Isaac Shiri;Ghasem Hajianfar;Ahmad Sohrabi;Hamid Abdollahi

  • Multi-level multi-modality (PET and CT) fusion radiomics: prognostic modeling for non-small cell lung carcinoma.

    Mehdi Amini;Mehdi Amini;Mostafa Nazari;Isaac Shiri;Ghasem Hajianfar

  • Next-Generation Radiogenomics Sequencing for Prediction of EGFR and KRAS Mutation Status in NSCLC Patients Using Multimodal Imaging and Machine Learning Algorithms

    Isaac Shiri;Hasan Maleki;Hasan Maleki;Ghasem Hajianfar;Hamid Abdollahi;Hamid Abdollahi

  • Non-Invasive Fuhrman Grading of Clear Cell Renal Cell Carcinoma Using Computed Tomography Radiomics Features and Machine Learning

    Mostafa Nazari;Isaac Shiri;Ghasem Hajianfar;Niki Oveisi

Frequent Co-Authors

Arman Rahmim
Arman Rahmim University of British Columbia
Amir Kasaeian
Amir Kasaeian Tehran University of Medical Sciences
Mohammad Abdollahi
Mohammad Abdollahi Tehran University of Medical Sciences

External Links

Personal website of Isaac Shiri

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Publications: 6

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Piotr J. Slomka

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Publications: 4

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Nguyen Quoc Khanh Le

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Publications: 4

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Publications: 4

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