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About the database ScholarIQanswers from OpenAlex & ORCID
How has Alhadi Almangush's publication output changed over time?
ScholarIQpublication output · 2013–2023
Output grew0% over the shown period — from 1 works in 2013 to 1 in 2023.
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20132014201520172019202120222023
What are the most-cited papers on Alhadi Almangush?
ScholarIQmost cited works
Depth of invasion, tumor budding, and worst pattern of invasion: Prognostic indicators in early‐stage oral tongue cancer
Alhadi Almangush, Ibrahim O. Bello, Harri Keski–Säntti, Laura K. Mäkinen, Joonas H. Kauppila, Matti Pukkila, Jaana Hagström, Jussi Laranne, Satu Tommola, Outi Nieminen, Ylermi Soini, Veli‐Matti Kosma, Petri Koivunen, Reidar Grénman, Ilmo Leivo, Tuula Salo
Head & Neck. 2013333 CitationsOPEN ACCESS
Prognostic biomarkers for oral tongue squamous cell carcinoma: a systematic review and meta-analysis
Alhadi Almangush, Ilkka Heikkinen, Antti Mäkitie, Ricardo D. Coletta, Esa Läärä, Ilmo Leivo, Tuula Salo
British Journal of Cancer. 2017221 CitationsOPEN ACCESS
Tumour budding in oral squamous cell carcinoma: a meta-analysis
Alhadi Almangush, Matti Pirinen, Ilkka Heikkinen, Antti Mäkitie, Tuula Salo, Ilmo Leivo
British Journal of Cancer. 2017202 CitationsOPEN ACCESS
Machine learning in oral squamous cell carcinoma: Current status, clinical concerns and prospects for future—A systematic review
Rasheed Omobolaji Alabi, Omar Youssef, Matti Pirinen, Mohammed Elmusrati, Antti Mäkitie, Ilmo Leivo, Alhadi Almangush
Artificial Intelligence in Medicine. 2021175 CitationsOPEN ACCESS
Machine learning explainability in nasopharyngeal cancer survival using LIME and SHAP
Rasheed Omobolaji Alabi, Mohammed Elmusrati, Ilmo Leivo, Alhadi Almangush, Antti Mäkitie
Scientific Reports. 2023154 CitationsOPEN ACCESS
Related on ScholarIQ
University of Helsinki
Institution
Depth of invasion, tumor budding, and worst pattern of invasion: Prognostic indicators in early‐stage oral tongue cancer
Paper
Prognostic biomarkers for oral tongue squamous cell carcinoma: a systematic review and meta-analysis
Paper
Tumour budding in oral squamous cell carcinoma: a meta-analysis
Paper
Machine learning in oral squamous cell carcinoma: Current status, clinical concerns and prospects for future—A systematic review
Paper
Machine learning explainability in nasopharyngeal cancer survival using LIME and SHAP
Paper