Thyroidkeeper: a healthcare management system for patients with thyroid diseases.

IF 4.7 3区医学 Q1 MEDICAL INFORMATICS Health Information Science and Systems Pub Date : 2023-10-17 eCollection Date: 2023-12-01 DOI:10.1007/s13755-023-00251-w

Jing Zhang, Jianhua Li, Yi Zhu, Yu Fu, Lixia Chen

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Abstract

Thyroid diseases, especially thyroid tumors, have a huge population in China. The postoperative patients, under China's incomplete tertiary diagnosis and treatment system, will frequently go to tertiary hospitals for follow-up and medication adjustment, resulting in heavy burdens on both specialists and patients. To help postoperative patients recover better against the above adverse conditions, a novel mobile application ThyroidKeeper is proposed as a collaborative AI-based platform that benefits both patients and doctors. In addition to routine health records and management functions, ThyroidKeeper has achieved several innovative points. First, it can automatically adjust medication dosage for patients during their rehabilitation based on their medical history, laboratory indicators, physical health status, and current medication. Second, it can comprehensively predict the possible complications based on the patient's health status and the health status of similar groups utilizing graph neural networks. Finally, the employing of graph neural network models can improve the efficiency of online communication between doctors and patients, help doctors obtain medical information for patients more quickly and precisely, and make more accurate diagnoses. The preliminary evaluation in both laboratory and real-world environments shows the advantages of the proposed ThyroidKeeper system.

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甲状腺守护者：甲状腺疾病患者的医疗管理系统。

甲状腺疾病，特别是甲状腺肿瘤，在中国人口众多。在我国不完善的三级诊疗体系下，术后患者会频繁前往三级医院随访和药物调整，给专家和患者带来沉重负担。为了帮助术后患者更好地恢复上述不良情况，提出了一种新的移动应用程序ThyroidKeeper，作为一个基于人工智能的协作平台，使患者和医生都受益。除了常规的健康记录和管理功能外，ThyroidKeeper还实现了几个创新点。首先，它可以根据患者的病史、实验室指标、身体健康状况和当前药物情况，自动调整患者康复期间的药物剂量。其次，它可以利用图神经网络，根据患者的健康状况和相似群体的健康状况，全面预测可能的并发症。最后，采用图神经网络模型可以提高医患之间的在线沟通效率，帮助医生更快、更准确地为患者获取医疗信息，并做出更准确的诊断。在实验室和现实世界环境中的初步评估显示了所提出的ThyroidKeeper系统的优势。

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来源期刊

Health Information Science and Systems MEDICAL INFORMATICS-

CiteScore

11.30

自引率

5.00%

发文量

期刊介绍： Health Information Science and Systems is a multidisciplinary journal that integrates artificial intelligence/computer science/information technology with health science and services, embracing information science research coupled with topics related to the modeling, design, development, integration and management of health information systems, smart health, artificial intelligence in medicine, and computer aided diagnosis, medical expert systems. The scope includes: i.) smart health, artificial Intelligence in medicine, computer aided diagnosis, medical image processing, medical expert systems ii.) medical big data, medical/health/biomedicine information resources such as patient medical records, devices and equipments, software and tools to capture, store, retrieve, process, analyze, optimize the use of information in the health domain, iii.) data management, data mining, and knowledge discovery, all of which play a key role in decision making, management of public health, examination of standards, privacy and security issues, iv.) development of new architectures and applications for health information systems.