mlsanityData to 7 Oct 2026

Deep Learning, Natural Language Processing, and Explainable Artificial Intelligence in the Biomedical Domain

arXiv 2202.12678 ↗First posted 25 Feb 2022cs.AI cs.CL cs.LGcited by 4

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Abstract (arXiv)

In this article, we first give an introduction to artificial intelligence and its applications in biology and medicine in Section 1. Deep learning methods are then described in Section 2. We narrow down the focus of the study on textual data in Section 3, where natural language processing and its applications in the biomedical domain are described. In Section 4, we give an introduction to explainable artificial intelligence and discuss the importance of explainability of artificial intelligence systems, especially in the biomedical domain.

Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). Builds on 33 of its 106 references that are in the map. First posted on arXiv 25 Feb 2022.

Builds on

33 of 106 references.

References · 33

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21 more
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Cited by year

Citing papers per year: 2023: 2; 2024: 0; 2025: 2.

4 papers.

  1. 2025Explainability in Practice: A Survey of Explainable NLP Across Various Domainscited by 11
  2. 2023Model-agnostic explainable artificial intelligence for object detection in image datacited by 6
  3. 2025MedVAL: Toward Expert-Level Medical Text Validation with Language Modelscited by 3
  4. 2023Explainable AI in Orthopedics: Challenges, Opportunities, and Prospectscited by 1