A study on optimizing the diagnostic and therapeutic communication model for pneumoconiosis care empowered by AI agent technology

DOAJ (DOAJ: Directory of Open Access Journals) · 2026-04-01

Objective To develop an AI agent dedicated to assisting the diagnosis and treatment of pneumoconiosis, improve clinical communication outcomes and treatment adherence, and promote precision prevention and control of pneumoconiosis. MethodsA cross-sectional study was conducted by recruiting 388 patients with pneumoconiosis in Guangdong Province. Behavioral characteristics and difficulties in this population were analyzed and incorporated into workflow scripts. Unstructured interviews were conducted with 4 patients, 2 respiratory physicians, 1 volunteer from a public welfare organization, and 1 occupational disease litigation attorney. Based on the questionnaire and interview results, an AI agent was developed on the Coze platform, and its effectiveness and advantages were evaluated through specialist physician assessment and comparison with the use of general-purpose large models. ResultsA total of 357 patients were ultimately included, of whom 344 were male (96.4%). Questionnaire results showed that, regarding disease cognition, patients’ treatment cognition was positively influenced only by educational level (B = 0.110, β = 0.163, P ＜ 0.01). Symptom cognition was influenced not only positively by educational level (B = 0.082, β = 0.112, P ＜ 0.05) but also negatively by hope level (B = −0.480, β = −0.190, P ＜ 0.001). The total cognition score was positively influenced by educational level (B = 0.192, β = 0.115, P ＜ 0.05) and negatively influenced by hope level (B = −0.754, β = −0.131, P ＜ 0.05). Regarding self-management capacity, female patients had higher self-management capacity than male patients (B = 6.875, β = 0.156, P ＜ 0.01). Educational level, disease stage, degree of media exposure, and hope level all showed positive effects (B = 0.519, β = 0.110, P ＜ 0.05; B = 1.134, β = 0.125, P ＜ 0.05; B = 0.782, β = 0.323, P ＜ 0.001; B = 2.090, β = 0.128, P ＜ 0.05). Unstructured interview results showed that many patients had passive information behaviors, lacked health education support from primary-level organizations, and had a structural imbalance in disease cognition; interviewees without pneumoconiosis generally considered that patients had certain problems in obtaining disease information and in physician-patient communication. The AI agent “E Xiaozhu”, developed to address these issues, includes the following core functions: knowledge-graph-based intelligent Q&A, standardized guidance for symptom self-assessment, generation of personalized health management plans, and pre-visit communication assistance. Two specialist physicians reported that “E Xiaozhu” has adequate reliability and scientific rigor. A comparison of human-AI interaction in response to specific diagnostic and therapeutic questions between the AI agent “E Xiaozhu” and general-purpose large models such as DeepSeek and Xinghuo showed that the AI agent can provide diagnostic and therapeutic information more directly from a specialist physician perspective, and offers emotional support, thereby facilitating patients’ active disease management. Therefore, the AI agent “E Xiaozhu” can optimize the diagnostic and therapeutic communication model by improving treatment efficiency and information completeness, considering patient needs, and analyzing complex lesions. ConclusionThe AI agent developed based on the cognitive and behavioral characteristics of patients with pneumoconiosis can assist in providing more comprehensive diagnosis and life advice, and to improve treatment and communication outcomes.

Perceived Government Statistics Reliability and Economic Expectations

AEA Randomized Controlled Trials · 2025-09-04

Potential role of rosemary in cardiovascular disease therapies: progress and promise

Traditional Medicine Research · 2025-01-01 · 1 citations

Targeting Lactic Acid Modification in Ischemic Heart Diseases: Novel Therapeutics and Mechanism

Journal of Cardiovascular Translational Research · 2025-02-07 · 7 citations

Perceived Government Statistics Reliability and Economic Expectations

AEA Randomized Controlled Trials · 2025-09-04

Robust Reversible Watermarking Scheme in Video Compression Domain Based on Multi-Layer Embedding

Electronics · 2024-09-20 · 2 citations

Most of the existing research on video watermarking schemes focus on improving the robustness of watermarking. However, in application scenarios such as judicial forensics and telemedicine, the distortion caused by watermark embedding on the original video is unacceptable. To solve this problem, this paper proposes a robust reversible watermarking (RRW)scheme based on multi-layer embedding in the video compression domain. Firstly, the watermarking data are divided into several sub-secrets by using Shamir’s (t, n)-threshold secret sharing. After that, the chroma sub-block with more complex texture information is filtered out in the I-frame of each group of pictures (GOP), and the sub-secret is embedded in that frame by modifying the discrete cosine transform (DCT) coefficients within the sub-block. Finally, the auxiliary information required to recover the coefficients is embedded into the motion vector of the P-frame of each GOP by a reversible steganography algorithm. In the absence of an attack, the receiver can recover the DCT coefficients by extracting the auxiliary information in the vectors, ultimately recovering the video correctly. The watermarking scheme demonstrates strong robustness even when it suffers from malicious attacks such as recompression attacks and requantization attacks. The experimental results demonstrate that the watermarking scheme proposed in this paper exhibits reversibility and high visual quality. Moreover, the scheme surpasses other comparable methods in the robustness test session.

Can Socially Assistive Robots Be Accepted by Older People Living Alone in the Community?: Empirical Findings from a Social Work Project in China

Journal of Gerontological Social Work · 2024-04-29 · 12 citations

A pilot study was undertaken between March 2019 and September 2021, loaning socially assistive robots (SARs) for a 7-day trial to older people living alone in China. Quantitative assessments of participants' acceptance of technology and loneliness were conducted before and after the intervention, supplemented with qualitative interviews. Unexpectedly, participants' intention to use SARs decreased significantly, largely due to emotional anxiety. Meanwhile, participants' level of loneliness remained unchanged. Follow-up interviews revealed anxious emotion, hesitant attitudes, unreal social presence, usability difficulties as contributing factors. The study provides social workers with valuable insights into introducing SARs into community care of older people.

Robust Watermarking Algorithm based on DCT Two-dimensional Histogram Shifting

2023-06-30

In order to solve the robustness problem of existing video watermarking algorithms, we propose a robust watermarking algorithm based on DCT coefficients. The algorithm groups the DCT coefficients generated by H.264 video coding according to the embedding efficiency and embeds the watermark by a reversible method to achieve watermark extraction at the decoding end and lossless recovery of the original video. The experimental results show that the proposed algorithm access great robustness, and the normalized correlation coefficient of each carrier video is above 0.949.

Lessons from Historical Epidemics, Pandemics, and Their Social Repercussions: Exploring Potential Scenarios for COVID-19

Mankind Quarterly · 2023-01-01 · 2 citations

The 2019 coronavirus disease (COVID-19) pandemic has resulted in much pain, loss of life, and social disruption. However, this is only the most recent epidemic. There have been several serious disease outbreaks and pandemics throughout history, including the Black Death, Spanish flu and SARS which brought devastating effects globally. This article places the COVID-19 pandemic into the wider context of previous pandemics. The study’s major objective is to compare the mortality rates, as well as the socioeconomic and demographic implications of the most recent pandemic, to prior pandemics. This provides the context that allows us to estimate future risks from pandemics. The research found that the mortality toll from the recent pandemic was not as high as it was during past pandemics such as the Black Death and the Spanish flu, not only because of the virus’ biology but also due to technological capabilities and efficacy of national health care systems, especially the timely provision of vaccines. Unlike some earlier pandemics that had vast impacts, COVID-19 was not an existential threat to human societies and human civilization. The conclusion is that while vigilance is required, future pandemics are unlikely to pose unmanageable threats as long as high standards of social order and medical knowledge and technology can be maintained. Keywords: History, Epidemics, Pandemics, Black Death, Covid-19

Boundedly rational information demand

AEA Randomized Controlled Trials · 2022-11-29