Tibetan Medical Named Entity Recognition Study for Tibetan Clinical Electronic Medical Records

Zhuoma, Cuo; Jia, Cairang; Duanzhu, Sangjie; Yangmao, Zhuoma; Zhuoma, Zhaxi

doi:10.2139/ssrn.4040676

Cited by 2 publications

(3 citation statements)

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“…Unfortunately, many corpora in LoE remain unavailable to the public for various reasons (ethics, data sensitivity, company policy, etc.). Nevertheless, they are often featured in publications that carry detailed and valuable information on the specificities of a particular LoE (Ukrainian [35]); the resource selection (Arabic [36]); the annotation process (Tibetan [37]), or the evaluation of different machine learning methods (French [38]).…”

Section: New Multilingual Resources and Monolingual Datasets In Loementioning

confidence: 99%

“…Non-segmented languages, such as Japanese, Chinese, or Tibetan, pose a real challenge to proper tokenization and NER. Leveraging multi-level representations can alleviate the loss of semantics caused by erroneous segmentation in non-segmented languages [37,56]. Wang et al [57] outperformed the current Chinese NER state-of-the-art by navigating character-and word-level trees via different-length paths in order to combine character representations with word and position embeddings.…”

Section: Named Entity Recognition Normalization and Linking For Loementioning

confidence: 99%

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Exploring the Latest Highlights in Medical Natural Language Processing across Multiple Languages: A Survey

Shaitarova,

Zaghir,

Lavelli

et al. 2023

Yearb Med Inform

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Objectives: This survey aims to provide an overview of the current state of biomedical and clinical Natural Language Processing (NLP) research and practice in Languages other than English (LoE). We pay special attention to data resources, language models, and popular NLP downstream tasks. Methods: We explore the literature on clinical and biomedical NLP from the years 2020-2022, focusing on the challenges of multilinguality and LoE. We query online databases and manually select relevant publications. We also use recent NLP review papers to identify the possible information lacunae. Results: Our work confirms the recent trend towards the use of transformer-based language models for a variety of NLP tasks in medical domains. In addition, there has been an increase in the availability of annotated datasets for clinical NLP in LoE, particularly in European languages such as Spanish, German and French. Common NLP tasks addressed in medical NLP research in LoE include information extraction, named entity recognition, normalization, linking, and negation detection. However, there is still a need for the development of annotated datasets and models specifically tailored to the unique characteristics and challenges of medical text in some of these languages, especially low-resources ones. Lastly, this survey highlights the progress of medical NLP in LoE, and helps at identifying opportunities for future research and development in this field.

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Section: New Multilingual Resources and Monolingual Datasets In Loementioning

confidence: 99%

Section: Named Entity Recognition Normalization and Linking For Loementioning

confidence: 99%

Exploring the Latest Highlights in Medical Natural Language Processing across Multiple Languages: A Survey

Shaitarova,

Zaghir,

Lavelli

et al. 2023

Yearb Med Inform

View full text Add to dashboard Cite

show abstract

“…According to incomplete statistics, there are a total of 436,000 Tibetan literary works in cultural institutions and religious sites throughout China. [6]Among existing studies, there are few papers that explore the techniques, materials, colors, and symbolic meanings of Tibetan costumes using Tibetan literary sources. This remains a major untapped research area in the cultural study of Tibetan costumes.…”

Section: Research On the Transmission Of Traditional Tibetan Costume ...mentioning

confidence: 99%

Research on the Innovation Path of Tibetan Ethnic Dress Culture Communication

2023

IJFS

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Tibetan costume culture is a treasure of Chinese ethnic costume culture. Through clothing patterns and production techniques, it demonstrates the "unity in diversity" of Chinese culture and has important significance for building a discourse system of "cultural confidence" in our country. In modern society, the transmission of Tibetan costume culture has shifted from the "apprenticeship-style" inheritance based on kinship relationships to the employment of apprentices. With economic development, major universities and vocational schools have cultivated fashion design students, and on-the-job training in modern factories has also gradually become standardized. In addition, fashion shows, images, short videos, and livestreaming have gradually become mainstream modes of transmission through new media. This article investigates the inheritance of Tibetan ethnic costume culture and discusses how to pass down intangible cultural heritage costume culture of ethnic minorities in a modern context. It analyzes the risks of generational breaks in inheritance due to the impact of industrialization, with young inheritors being influenced by economic and social status. It proposes solutions such as constructing a social support system, understanding consumer trends, leveraging design as a force, and promoting "social aesthetics." It also analyzes the inheritance of intangible cultural heritage costume by inheritors, audiences, and consumers, as well as the possibilities for continuous innovation.

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Tibetan Medical Named Entity Recognition Study for Tibetan Clinical Electronic Medical Records

Cited by 2 publications

References 0 publications

Exploring the Latest Highlights in Medical Natural Language Processing across Multiple Languages: A Survey

Exploring the Latest Highlights in Medical Natural Language Processing across Multiple Languages: A Survey

Research on the Innovation Path of Tibetan Ethnic Dress Culture Communication

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