Research Article
Thoughts on the Design and Development of Artificial Intelligence for Traditional Chinese Medicine Clinical Decision Making in Community Hospitals
Xiaoqing Zhang*
Issue:
Volume 14, Issue 2, April 2026
Pages:
18-23
Received:
26 February 2026
Accepted:
26 March 2026
Published:
13 April 2026
Abstract: The rapid development of artificial intelligence (AI) technology has opened up a new path for the development of community traditional Chinese medicine (TCM) diagnosis and treatment. By introducing intelligent auxiliary decision-making systems, the clinical diagnosis and treatment capabilities of grassroots TCM practitioners can be effectively enhanced, making up for their relatively insufficient experience. However, at present, the application of this technology in the TCM field still faces many challenges. Its algorithm models and knowledge systems need to be deeply integrated with the theoretical characteristics of TCM, such as the holistic view and syndrome differentiation and treatment, as well as the flexible and adaptable clinical practice requirements. It is necessary to actively explore feasible integration solutions in the real clinical decision-making process. This article systematically analyzes the current development status of community TCM clinics and the specific application of AI technology in areas such as auxiliary diagnosis and prescription recommendation. It focuses on sorting out the practical problems existing in core links such as the standardization and unification of TCM terms, modeling of syndrome differentiation and treatment processes, screening and compatibility of prescriptions, and dosage and contraindications of drugs. On this basis, it deeply explores how to design and develop a relatively complete and human-machine collaborative intelligent auxiliary decision-making system, and proposes optimization paths from multiple dimensions such as strengthening humanistic care, adhering to medical ethics, and ensuring data security. Finally, it provides systematic solutions for promotion from three aspects: strengthening cross-disciplinary scientific research, promoting the popularization of technology and knowledge education, and improving industry standards and policy guidance, with the aim of providing practical theoretical basis and practical reference for the in-depth empowerment of grassroots TCM services by AI.
Abstract: The rapid development of artificial intelligence (AI) technology has opened up a new path for the development of community traditional Chinese medicine (TCM) diagnosis and treatment. By introducing intelligent auxiliary decision-making systems, the clinical diagnosis and treatment capabilities of grassroots TCM practitioners can be effectively enha...
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Review Article
The Butterfly Code: A Mechanistic Review of Thyroid Antibodies
Chaimaa Zeroual*,
Safaa Mourabit,
Mina Moudatir,
Khadija Echchilali,
Leila Barakat,
Hassan Elkabli
Issue:
Volume 14, Issue 2, April 2026
Pages:
24-34
Received:
11 April 2026
Accepted:
21 April 2026
Published:
30 April 2026
DOI:
10.11648/j.sd.20261402.12
Downloads:
Views:
Abstract: Autoimmune thyroid diseases (AITDs) are common disorders marked by the presence of thyroid autoantibodies. This review summarizes their immunological roles, clinical relevance, and diagnostic value based on studies published up to January 2026. The main antibodies—anti-TPO, anti-Tg, and TSH receptor antibodies (TRAb) —serve different functions. TRAb play a direct pathogenic role, especially in Graves’ disease, while anti-TPO and anti-Tg are primarily markers associated with autoimmune thyroid destruction, such as in Hashimoto’s thyroiditis. Clinically, TRAb are important for diagnosis and monitoring of Graves’ disease, whereas anti-TPO and anti-Tg help identify autoimmune origin and assess the risk of hypothyroidism. However, their diagnostic accuracy is limited by their presence in some healthy individuals. Overall, thyroid autoantibodies remain essential tools in clinical practice, though careful interpretation is necessary. Future approaches combining immunology with computational methods may improve disease prediction and management.
Abstract: Autoimmune thyroid diseases (AITDs) are common disorders marked by the presence of thyroid autoantibodies. This review summarizes their immunological roles, clinical relevance, and diagnostic value based on studies published up to January 2026. The main antibodies—anti-TPO, anti-Tg, and TSH receptor antibodies (TRAb) —serve different functions. TRA...
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