José Bobes-Bascarán

795 total citations · 1 hit paper
7 papers, 383 citations indexed

About

José Bobes-Bascarán is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Health Informatics. According to data from OpenAlex, José Bobes-Bascarán has authored 7 papers receiving a total of 383 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Artificial Intelligence, 1 paper in Computer Vision and Pattern Recognition and 1 paper in Health Informatics. Recurrent topics in José Bobes-Bascarán's work include Machine Learning and Data Classification (5 papers), Explainable Artificial Intelligence (XAI) (5 papers) and Machine Learning and Algorithms (3 papers). José Bobes-Bascarán is often cited by papers focused on Machine Learning and Data Classification (5 papers), Explainable Artificial Intelligence (XAI) (5 papers) and Machine Learning and Algorithms (3 papers). José Bobes-Bascarán collaborates with scholars based in Spain and China. José Bobes-Bascarán's co-authors include David Alonso-Ríos, Eduardo Mosqueira-Rey, Elena Hernández-Pereira, Ángel Fernández-Leal and Vicente Moret‐Bonillo and has published in prestigious journals such as Neural Computing and Applications, Artificial Intelligence Review and MDPI (MDPI AG).

In The Last Decade

José Bobes-Bascarán

7 papers receiving 366 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.

Human-in-the-loop machine learning: a state of the art

2022 347 citations Eduardo Mosqueira-Rey, Elena Hernández-Pereira et al. Artificial Intelligence Review profile →

Peers

Countries citing papers authored by José Bobes-Bascarán

Since Specialization

Citations

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

Fields of papers citing papers by José Bobes-Bascarán

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by José Bobes-Bascarán. 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 José Bobes-Bascarán. The network helps show where José Bobes-Bascarán may publish in the future.

Co-authorship network of co-authors of José Bobes-Bascarán

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

All Works

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7 of 7 papers shown

#	Work	Indexed citations
1	Understanding Machine Learning Explainability Models in the context of Pancreatic Cancer Treatment 2023 ·José Bobes-Bascarán, (unknown), Eduardo Mosqueira-Rey, David Alonso-Ríos, Elena Hernández-Pereira, Vicente Moret‐Bonillo	2
2	Addressing the data bottleneck in medical deep learning models using a human-in-the-loop machine learning approach 2023 ·Neural Computing and Applications ·Eduardo Mosqueira-Rey, Elena Hernández-Pereira, José Bobes-Bascarán, David Alonso-Ríos, (unknown), Ángel Fernández-Leal, Vicente Moret‐Bonillo, (unknown), (unknown)	10
3	Human-in-the-Loop Machine Learning for the Treatment of Pancreatic Cancer 2023 ·RUC (Universidade Da Coruña) ·Eduardo Mosqueira-Rey, (unknown), Elena Hernández-Pereira, David Alonso-Ríos, José Bobes-Bascarán, Ángel Fernández-Leal, Vicente Moret‐Bonillo, (unknown), (unknown)	8
4	Using Active Learning to Improve the Treatment Selection on Pancreatic Cancer Patients 2023 ·José Bobes-Bascarán, (unknown), Eduardo Mosqueira-Rey, David Alonso-Ríos, Elena Hernández-Pereira	1
5	Human-in-the-loop machine learning: a state of the art breakdown → 2022 ·Artificial Intelligence Review ·Eduardo Mosqueira-Rey, Elena Hernández-Pereira, David Alonso-Ríos, José Bobes-Bascarán, Ángel Fernández-Leal	347
6	A classification and review of tools for developing and interacting with machine learning systems 2022 ·Proceedings of the 37th ACM/SIGAPP Symposium on Applied Computing ·Eduardo Mosqueira-Rey, Elena Hernández-Pereira, David Alonso-Ríos, José Bobes-Bascarán	12
7	Improving Medical Data Annotation Including Humans in the Machine Learning Loop 2021 ·MDPI (MDPI AG) ·José Bobes-Bascarán, Eduardo Mosqueira-Rey, David Alonso-Ríos	3

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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