Alfonso Medela

619 total citations · 1 hit paper
15 papers, 402 citations indexed

About

Alfonso Medela is a scholar working on Surgery, Artificial Intelligence and Dermatology. According to data from OpenAlex, Alfonso Medela has authored 15 papers receiving a total of 402 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Surgery, 5 papers in Artificial Intelligence and 4 papers in Dermatology. Recurrent topics in Alfonso Medela's work include AI in cancer detection (5 papers), Head and Neck Cancer Studies (3 papers) and Salivary Gland Tumors Diagnosis and Treatment (3 papers). Alfonso Medela is often cited by papers focused on AI in cancer detection (5 papers), Head and Neck Cancer Studies (3 papers) and Salivary Gland Tumors Diagnosis and Treatment (3 papers). Alfonso Medela collaborates with scholars based in Spain, Italy and Belgium. Alfonso Medela's co-authors include Artzai Picón, Arantza Bereciartúa-Pérez, Aitor Álvarez-Gila, Unai Irusta, Carlos M. Chiesa‐Estomba, Riccardo Cicchi, Cristina L. Saratxaga, Ben Glover, Roberto Bilbao and Ramón Grimalt and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Access and Journal of the American Academy of Dermatology.

In The Last Decade

Alfonso Medela

14 papers receiving 381 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.

Few-Shot Learning approach for plant disease classification using images taken in the field

2020 248 citations Artzai Picón, Unai Irusta et al. Computers and Electronics in Agriculture profile →

Peers

Countries citing papers authored by Alfonso Medela

Since Specialization

Citations

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

Fields of papers citing papers by Alfonso Medela

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Alfonso Medela

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

All Works

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15 of 15 papers shown

#	Work	Indexed citations
1	Artificial Intelligence‐Based Quantification to Assess the Automatic Psoriasis Area and Severity Index 2025 ·JEADV Clinical Practice ·(unknown), (unknown), Alfonso Medela, (unknown), (unknown), Antonio Martorell, (unknown), Gastón Roustán	0
2	The utility and reliability of a deep learning algorithm as a diagnosis support tool in head & neck non-melanoma skin malignancies 2024 ·European Archives of Oto-Rhino-Laryngology ·Alfonso Medela, (unknown), (unknown), (unknown), Andres Aguilar, Carlos M. Chiesa‐Estomba	2
3	Automatic International Hidradenitis Suppurativa Severity Score System (AIHS4): A novel tool to assess the severity of hidradenitis suppurativa using artificial intelligence 2023 ·Skin Research and Technology ·(unknown), Alfonso Medela, (unknown), (unknown), (unknown), (unknown), (unknown), (unknown), (unknown), (unknown), Fernando Alfageme	13
4	Automatic Urticaria Activity Score: Deep Learning–Based Automatic Hive Counting for Urticaria Severity Assessment 2023 ·SHILAP Revista de lepidopterología ·(unknown), (unknown), (unknown), (unknown), (unknown), (unknown), (unknown), Fernando Alfageme, Alfonso Medela	3
5	Facial nerve palsy following parotid gland surgery: A machine learning prediction outcome approach 2023 ·World Journal of Otorhinolaryngology - Head and Neck Surgery ·Carlos M. Chiesa‐Estomba, José Ángel González-García, Ekhiñe Larruscain, (unknown), Miquel Quer, Xavier León, (unknown), (unknown), Miguel Mayo‐Yáñez, Alfonso Medela	1
6	Automatic SCOring of Atopic Dermatitis Using Deep Learning: A Pilot Study 2022 ·SHILAP Revista de lepidopterología ·Alfonso Medela, (unknown), (unknown), Carlos M. Chiesa‐Estomba, Ramón Grimalt	21
7	Machine Learning Algorithms as a Computer-Assisted Decision Tool for Oral Cancer Prognosis and Management Decisions: A Systematic Review 2022 ·ORL ·Carlos M. Chiesa‐Estomba, Manuel Graña, Alfonso Medela, (unknown), Jérôme R. Lechien, Christian Calvo‐Henríquez, Miguel Mayo‐Yáñez, Luigi Angelo Vaira, Alberto Grammatica, Giovanni Cammaroto, Tareck Ayad, Johannes J. Fagan	13
8	Dermatology Image Quality Assessment (DIQA): Artificial intelligence to ensure the clinical utility of images for remote consultations and clinical trials 2022 ·Journal of the American Academy of Dermatology ·(unknown), (unknown), Andres Aguilar, Alfonso Medela	4
9	Automatic International Hidradenitis Suppurativa Severity Score System (AIHS4): A Novel Tool to Assess the Severity of Hidradenitis Suppurativa Using Artificial Intelligence 2022 ·SSRN Electronic Journal ·(unknown), Alfonso Medela, (unknown), Andres Aguilar, (unknown), (unknown), (unknown), (unknown), (unknown), (unknown), Fernando Alfageme	1
10	Autofluorescence Image Reconstruction and Virtual Staining for In-Vivo Optical Biopsying 2021 ·IEEE Access ·Artzai Picón, Alfonso Medela, Luisa F. Sánchez‐Peralta, Riccardo Cicchi, Roberto Bilbao, Domenico Alfieri, Andoni Elola, Ben Glover, Cristina L. Saratxaga	15
11	Machine Learning Models for Predicting Facial Nerve Palsy in Parotid Gland Surgery for Benign Tumors 2021 ·Journal of Surgical Research ·Carlos M. Chiesa‐Estomba, (unknown), (unknown), José Ángel González-García, Ekhiñe Larruscain, Xabier Altuna, Alfonso Medela, Manuel Graña	14
12	Constellation Loss: Improving the Efficiency of Deep Metric Learning Loss Functions for the Optimal Embedding of histopathological images 2020 ·Journal of Pathology Informatics ·Alfonso Medela, Artzai Picón	20
13	Artificial Neural Network as a Tool to Predict Facial Nerve Palsy in Parotid Gland Surgery for Benign Tumors 2020 ·SHILAP Revista de lepidopterología ·Carlos M. Chiesa‐Estomba, (unknown), José Ángel González-García, Ekhiñe Larruscain, Giovanni Cammaroto, Miguel Mayo‐Yáñez, Jérôme R. Lechien, Christian Calvo‐Henríquez, Xabier Altuna, Alfonso Medela	4
14	Few-Shot Learning approach for plant disease classification using images taken in the field breakdown → 2020 ·Computers and Electronics in Agriculture ·(unknown), Artzai Picón, Unai Irusta, Alfonso Medela, (unknown), Arantza Bereciartúa-Pérez, Aitor Álvarez-Gila	248
15	Few Shot Learning in Histopathological Images:Reducing the Need of Labeled Data on Biological Datasets 2019 ·TECNALIA Publications (Fundación TECNALIA Research & Innovation) ·Alfonso Medela, Artzai Picón, Cristina L. Saratxaga, (unknown), (unknown), Riccardo Cicchi, Roberto Bilbao, Ben Glover	43

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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