China Digital Medicine

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15 December 2025, Volume 20 Issue 12

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Research progress and trends in digital therapeutics applications

LIU Yuhan, CHENG Yaping, YU Siwei, LU Long

2025, 20(12): 1-8.

Abstract ( ) Knowledge map Save

This study systematically reviews the fundamental concepts and core values of digital therapeutics, and

comprehensively analyzes its current development landscape both globally and within China, focusing on regulatory

frameworks, product typologies, and application domains. Furthermore, it identifies the major challenges that constrain

DTx development, including insufficient clinical validation, limited patient adherence, incomplete reimbursement

mechanisms, and data security vulnerabilities. Based on existing literature, the paper proposes strategic countermeasures

to address these barriers and discusses future development trends in technological integration, policy support, and

market expansion. The review aims to offer theoretical foundations and practical references for the clinical application

and health policy formulation of digital therapeutics.
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Analysis of digital therapeutics products characteristics in the US, Germany, and Belgium with implications for China

XIANG Peng, FANG Qichuan, LEI Jianbo

2025, 20(12): 9-18.

Abstract ( ) Knowledge map Save

Objective To analyze the characteristics of approved Digital Therapeutics (DTx) products in the US,

Germany, and Belgium, providing references for the development of China's DTx industry. Methods Data were

sourced from the US FDA, German DiGA directory, and Belgian mHealthBELGIUM platform. Devices meeting the

DTx definition were identified based on inclusion and exclusion criteria, and their characteristics were analyzed using

descriptive statistics. Results By the end of 2024, a total of 272 DTx devices were included (US: 192; Germany: 55;

Belgium: 25). Following a period of fluctuating growth, the approval rates in all three countries showed a slowdown

in the past year. US products primarily focused on chronic disease management, largely leveraging mobile health
technologies. German products were concentrated on treating mental and behavioral disorders, predominantly

using cognitive behavioral therapy. Belgian products emphasized health status monitoring in oncology and chronic

diseases. Conclusion China should draw on these international experiences to improve its regulatory and payment

systems, strengthen real-world evidence and clinical value verification, and promote the standardized and sustainable

development of the DTx industry.
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Clinical applications, challenges, and prospects of digital therapeutics in insomnia

IANG Jiahui, YAO Pan, HUANG Lei.

2025, 20(12): 19-26.

Abstract ( ) Knowledge map Save

Insomnia, as the most common sleep disorder, faces challenges in traditional psychological treatment

due to resource constraints, high costs, and limited accessibility, making it difficult to meet clinical demands. Digital

therapeutics for insomnia (DTI) has consequently emerged, leveraging technologies such as mobile applications and

online platforms to transform diverse application formats or theoretical treatment methods into flexible and accessible

digital intervention solutions. DTI has a significant effect on improving insomnia and is cost-effective. However,

the field still faces a series of challenges, including limited applicability across specific populations, suboptimal

patient adherence, insufficient data security and regulatory frameworks, a lack of long-term efficacy evidence, and a

homogeneity in intervention models. Future efforts should prioritize the creation of diversified intervention pathways,

establish stepped-care models, and strengthen policy support and standardization efforts. These measures are essential to

achieving sustainable clinical utility and commercial value for DTI.
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The application and prospects of digital therapies in clinical nutritional intervention of foods for special medical purpose

LIU Li, WANG Yingyu, ZHU Mengting, LI Dan, SUN Jing, YAN Jiai, YANG Ju, ZHANG Feng, CAO Hong

2025, 20(12): 27-34.

Abstract ( ) Knowledge map Save

This article systematically collates the integrated application practices of DTx and FSMP in typical

chronic disease areas, including diabetes, post-chemoradiotherapy rehabilitation of tumors, chronic kidney disease,

and sarcopenia. It further conducts an in-depth analysis of core challenges in their synergistic development, such

as regulatory system adaptation, clinical validation standards, and data security governance, while outlining future

technological iterations and development trajectories. The in-depth integration of DTx and FSMP is capable of

transforming clinical nutrition from a standardized supply model to a dynamic targeted intervention paradigm. With

the maturation of relevant technologies and the improvement of supporting mechanisms, this integration is expected

to become a “standard configuration” for nutritional intervention in chronic diseases, providing crucial support for the

construction of a data-driven precision nutrition system.
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International experience and insights on the regulation of digital therapeutics applications

WU Lantao, ZHENG Qiuying, QIU Yingpeng, TIAN Xueqing, REN Ping, SHI Shenghui, XIAO Yue, YOU Mao.

2025, 20(12): 35-43.

Abstract ( ) Knowledge map Save

Objective To summarize the experiences of Germany, the United Kingdom, the United States, and

Japan in regulating the application of digital therapeutics, providing reference for improving relevant management

systems in China. Methods Information from the official websites of regulatory authorities in the four countries was

retrieved to sort out their policy frameworks and practical models. Results Germany ensures the quality of digital

therapeutics products through a dedicated directory management mechanism; the UK integrates health technology

assessment comprehensively into the regulatory process to ensure service safety and quality; the US implements a

Software Precertification Pilot Program, focusing on evaluating manufacturers' capabilities and product safety; Japan

implements the DASH strategy, adopting risk-based classification and dual regulation to strengthen product safety

and efficacy. Conclusion China can draw on international experience to establish flexible registration, approval,

and directory management mechanisms, improve the hierarchical classification system, construct a full-cycle health

technology assessment framework, enhance full-process supervision before and after market launch, standardize

prescription rights certification and management, establish a scientific pricing mechanism, and explore diversified
payment methods, thereby promoting the standardized and healthy development of digital therapeutics and better

serving patients' health needs.
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Construction and application of the refined management mode of medical consumables in whole-life cycle based on UDI

WANG Tingting, LIANG Weixia, HUANG Beili

2025, 20(12): 44-48、109.

Abstract ( ) Knowledge map Save

Objective To construct the refined management system of the whole-life cycle for medical consumables

based on unique device identification (UDI), and to address the challenges of extensive management of consumables.

Methods By upgrading the consumables information management system, the UDI code management module was

integrated in the supply chain platform, HIS, HRP, surgical anesthesia and SPD systems to promote multi-system

information interconnection. Qualitative and quantitative research methods were used to compare the management

efficiency indicators before and after UDI implementation. Results The application of UDI optimized the management

efficiency of medical consumables in acceptance, inventory, use, charge, settlement, traceability and other aspects, and

the acceptance warehousing time and billing time of consumables were substantially reduced (P＜0.001). Conclusion

The implementation of UDI system is helpful to realize the closed-loop tracking of the whole process data of medical

consumables, and provides key support for the refined transformation of consumables management.
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Ideas and practice for managing medical record connotation quality based on large language models

HOU Jie, LIU Ting, DUAN Congzhe.

2025, 20(12): 49-54.

Abstract ( ) Knowledge map Save

Objective To explore the application of large language models (LLMs) in the connotative quality

management of medical records and analyze the facilitative effect of emerging technologies on medical quality

improvement. Methods Using the "Quality Control Indicators for Medical Record Management (2021 Edition)"as

the target indicators to be evaluated in this study. LLMs were deeply integrated with the clinical decision support

system (CDSS), and structured desensitized medical data was utilized to train the model's proficiency in medical

record text comprehension. Through functions such as real-time in-process reminders and natural language interaction,

physicians were assisted in promptly detecting and rectifying connotative quality defects during the documentation

process. The clinical application accuracy of LLMs was verified by comparing the connotative quality control defects

identified by the model with manual adjudication results. Results All eight established connotative quality control

rules achieved an accuracy rate exceeding 90% during the experiment, and three target indicators were improved, which

was consistent with the experimental hypotheses. Conclusion LLMs exhibit superior capabilities over traditional

artificial intelligence (AI) quality control systems in medical record quality management. They contribute to enhancing

the connotative quality of medical records, strengthening physicians' awareness of documentation standardization,

significantly alleviating the workload of clinical staff, quality control personnel, and medical record administrators,

promoting the further optimization of the hospital's medical record quality management system, and aligning with the

overall goal of high-quality hospital development.
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Construction and practice of a multi-campus medical imaging data integration and intelligent diagnosis platform

QUE Jianren, LING Sikai.

2025, 20(12): 55-61.

Abstract ( ) Knowledge map Save

Objective It effectively integrated and utilized medical imaging data across various hospital campuses,

established a unified management standard for such data, so as to build a secure and efficient medical imaging data

integration and intelligent diagnosis platform. Methods Based on a privatized platform architecture, distributed storage

technology was adopted to achieve unified management of petabyte-level imaging data across multiple campuses. The

DICOM standard and FHIR protocol were utilized for standardized and fusion of multimodal data (CT, MRI, ultrasound,

endoscopy, nuclear medicine, etc.). Blockchain technology was implemented to ensure data security and privacy

protection. Deep learning-based intelligent diagnosis modules (3D ResNet and Transformer models) were deployed to

provide lesion detection, segmentation, and assisted diagnosis functions. Results The platform successfully integrated

imaging data from hospitals within the Ruijin Medical Consortium, enabling second-level retrieval of cross-campus

imaging data. The intelligent diagnosis module achieved over 96% accuracy in detecting typical conditions such as

pulmonary nodules, stroke, and fractures, with performance exceeding traditional methods by over 15%. Conclusion

The platform enables efficient fusion and intelligent application of multi-campus medical imaging data, significantly
enhancing clinical diagnostic efficiency and scientific research capabilities. It offers a scalable solution for regional

medical resource sharing and smart hospital construction.
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Research progress of artificial intelligence in difficult airway assessment

SONG Changwei, CHEN Yining, ZHAO Qing, LI Jianqiang, GE Yanhu, BAI Yunbo, BAI Jing, WANG Sheng, YANG Jijiang.

2025, 20(12): 61-68.

Abstract ( ) Knowledge map Save

In the field of anesthesiology, the occurrence of difficult airways significantly increases the likelihood of
various complications, posing substantial challenges to patient safety. Preoperative assessment of difficult airways helps

mitigate potential risks associated with them. However, current assessments heavily rely on the evaluator's personal

experience and professional skill level, leading to subjective variability and potential inconsistency in results. The

application of artificial intelligence (AI) in difficult airway assessment offers the ability to process and analyze vast

amounts of data, reducing subjectivity, minimizing inter-evaluator discrepancies, lowering the risk of human error, and

providing decision support. This review aims to comprehensively examine the application and research progress of

AI technologies in the evaluation of difficult airways within the anesthesiology field over the past five years, covering

the most advanced technologies and relevant literature. Additionally, this paper discusses the challenges faced by AI

applications in this domain and explores future development directions.
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Innovative application of digital diagnosis in metabolic syndrome based on fusion of infrared thermography and radiomics

GUO Jiayang, AN Yanhong, ZHANG Wenzheng, LI Xiaoran, CHEN Yu, XUE Huizhong, YANG Yimeng, XIAO Yonghua.

2025, 20(12): 69-74、115.

Abstract ( ) Knowledge map Save

Objective Develop a radiomics-based auxiliary diagnostic model for metabolic syndrome (MS)

using hand thermal infrared imaging combined with machine learning techniques, enabling early screening and

clinical decision support for MS. Methods Retrospective thermal infrared imaging data of 160 male subjects were

collected between July 2017 and April 2023 and divided into a training set and a validation set in a 7:3 ratio. Features

significantly associated with MS were identified using Pearson correlation analysis and LASSO regression, followed by

the construction of a random forest prediction model. The SHAP (SHapley Additive exPlanations) method was applied

to interpret the model and quantify the contribution of each feature to the prediction outcomes. Results Among the

160 male subjects, 80 were healthy controls and 80 were MS patients. The constructed radiomics model achieved an
AUC of 0.88 in the training set and 0.85 in the validation set, demonstrating robust diagnostic performance. The SHAP

analysis revealed the relevance of the original images, as well as the clustering tendency and contrast characteristics of

the LBP feature maps within the model. Conclusion The radiomics model based on palm thermal infrared imaging

provides a novel non-invasive approach for early MS screening. It exhibits excellent clinical application potential and

can effectively assist physicians in early intervention and clinical decision-making.
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Construction of an objective auxiliary evaluation system for non-specific low back pain posture data based on the holistic concept of Traditional Chinese Medicine

YAN Wei, JIANG Yongmei, XU Cheng, LIU Kuan, ZHANG Jiahui, MA Honghong, ZHAO Yichen, CHENG Shunda, FANG Min, XI Xiaobing.

2025, 20(12): 75-81.

Abstract ( ) Knowledge map Save

Objective To address the issue of subjective assessment of non-specific low back pain in clinical

practice, a non-specific low back pain efficacy auxiliary evaluation system based on dynamic functional analysis

under the guidance of the holistic concept of traditional Chinese medicine is proposed, promoting the development

of diagnosis and treatment of non-specific low back pain towards a more systematic and objective direction, and

improving the evaluation level of non-specific low back pain. Methods Collect dynamic functional data of patients

through motion capture and other technologies, develop intelligent motion hardware systems and supporting intelligent

diagnosis and treatment software, and achieve real-time and accurate collection and synchronous analysis of dynamic

functional data of non-specific low back pain patients. Research on data mining algorithms for mechanical information

characteristics of non-specific low back pain patients, revealing their matching patterns with functional models of non

specific low back pain patients, and achieving precise and objective evaluation of patients with this disease. To ensure

the accuracy and systematicity of the evaluation system, clinical validation will be conducted to analyze the evaluation

effect through feedback of biomechanical information and clinical comparison. Results This study designed an

objective auxiliary evaluation system for non-specific low back pain posture data, and found through clinical validation

that the A-GCN+MS-TCN model was significantly better than the traditional ST-GCN model in walking and motor

function testing of non-specific low back pain patient skeleton datasets, with significantly improved recognition

accuracy. Conclusion The objective auxiliary evaluation system for non-specific low back pain posture data based on

the holistic concept of traditional Chinese medicine has achieved precise collection of limb function data information,

which can improve the accuracy of clinical evaluation.
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Analysis of data reporting quality on the national clinical improvement system in 2020－2022

LIU Dong, PENG Qian, YANG Yang

2025, 20(12): 82-87.

Abstract ( ) Knowledge map Save

Objective To understand the quality of data reporting in the national clinical improvement system of

medical institutions, guide medical institutions to continuously improve the quality of data reporting, promote the high

quality development of hospitals, and provide a reference for relevant departments to formulate policies. Methods

Based on the data released by the National Clinical Improvement system from 2020 to 2022, we analyzed the

completeness of medical institutions, the overall “/” rate, the total star rating score, and differences in the type, level, and

ownership of medical institutions in the full sample from 2022. Results From 2020 to 2022, there were statistically

significant differences in the completeness, overall “/” rate, and total star rating of medical institutions (P ＜ 0.001).

In 2022, there were statistically significant differences in the type, level, and ownership between medical institutions

that had submitted data and those that had not submitted (P＜0.01). Conclusion Medical institutions should further

improve data filling and data quality control, and further reduce the overall “/” rate and improve the total star rating

while ensuring integrity. Improving the submission rate of medical institutions and strengthening the management of

data quality in specialized, level 2 and private medical institutions are the key to improving data quality.
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Research and exploration on enhancing hospital network security operations capability based on large model technology

SUN Guoqiang, LI Xiaoze, YANG Wei, HU Chenjie.

2025, 20(12): 87-92.

Abstract ( ) Knowledge map Save

Objective This study addresses issues such as difficulty in vulnerability repair, high data leakage

risks, and frequent attacks in cybersecurity operations within the healthcare sector. We aim to create an intelligent

security operation system based on large model technology to automate threat assessment and enhance cybersecurity
defense effectiveness. Methods We integrate dynamic rule generation with multimodal data fusion technology to

design a layered collaborative architecture known as "Situation Awareness － Large Model", which is then validated

in a real hospital environment. Results The security large models exhibited significant improvements compared to

traditional cybersecurity systems in core healthcare scenarios, with alert noise reduction rising from 56.7% to 92.6%,

and threat response times reduced to seconds, along with a substantial decrease in phishing email false positive rates.

Conclusion Intelligent security operation system based on large model technology provided reusable industry

solutions for the healthcare industry, promoting deep integration of AI and cybersecurity, and offering a reference path

for addressing cybersecurity challenges in the healthcare sector.
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Construction and practice of cybersecurity and boundary protection system in multi-campus hospitals

MA Liming, HUANG Shaobin, JIANG Zhuobin, HUANG Guoxing, ZHANG Xinghua.

2025, 20(12): 93-98.

Abstract ( ) Knowledge map Save

Objective This paper provides a practical reference for constructing a network security system for

medical institutions facing challenges in multi-campus and diverse information systems environments. Methods

The system adheres to the “Information Security Technology－Baseline for Classified Protection of Cybersecurity”

standard, employing a refined partitioned and zoned network architecture, combines high performance with highly

available critical path design, integrates multi-level mature security protection technology and normalized network

security operation, and constructs a unified security assurance system for multiple hospital areas. Results The

system's effectiveness has been validated through multiple attack-defense drills, which promotes internal management

and technical upgrading. Conclusion The successful establishment of an integrated architecture for network and

information security across multi-campus hospitals enables centralized management of security incidents, enhances

business continuity and security, and provides reference for the construction of cybersecurity systems in healthcare

institutions.
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Research on data security protection of China's disease prevention and control information system

DU Xuejie, LI Shaoqiong, JIN Lizhu, ZHENG Huan, GUO Qing

2025, 20(12): 99-102.

Abstract ( ) Knowledge map Save

Objective To address the increasingly serious data security issues faced by China's disease prevention

and control information system. Methods Analyze the current situation of data security in the system, explore data

security protection measures according to the relevant requirements of national data security. Results Establish

and implement a variety of data security mechanisms to effectively prevent data loss and leakage in the system.

Conclusion Effective protection of system data security is a prerequisite for high-quality development of disease

control information and a reference basis for public health data security management.
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Construction and application of pre-hospital emergency resource management platform based on global quality control management

ZHANG Zhelai, TANG Jingyun, ZHU Jie

2025, 20(12): 103-109.

Abstract ( ) Knowledge map Save
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Design and implementation of syndromic surveillance system based on large language model

ZHANG Zhelai, TANG Jingyun, ZHU Jie.

2025, 20(12): 110-115.

Abstract ( ) Knowledge map Save

Objective Symptom surveillance is of great significance for the early warning of infectious diseases

and public health emergencies. The existing symptom surveillance systems still rely on rule-based natural language

processing technology, which is difficult to obtain high precision symptom recognition rate and affects the reliability

and final effect of symptom surveillance. Methods A symptom monitoring system was designed and constructed

based on the Suzhou Universal Health Information Platform. This system applied the large language model technology

to the task of symptom entity recognition, specifically to identify symptoms in outpatient and emergency electronic

medical records by fine-tuned BERT pre-training model. Results The introduction of large language model technology

greatly improved the recall rate and accuracy rate of symptom recognition. Conclusion This system realized the high

precision symptom monitoring of T+1 day in outpatient and emergency departments of public medical institutions in the

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