Clinical eHealth最新文献

The emergence of the Medical Internet of Things (MIoT) has presented an opportune solution to these problems, as it provides effective technological support. Based on the current MIoT theory, it is feasible to realize efficient and accurate graded diagnosis and treatment through the linkage between doctors in large hospitals (the ‘Cloud Experts’) and doctors in small hospitals (the ‘Terminal Doctors’), and to contribute to the research and development of related technologies to improve graded diagnosis and treatment in China. Nevertheless, the following issues remain in clinical practice: (1) The Cloud Experts are not available to dedicate themselves to popular science education, or to give professional lectures, at all times and in all settings. (2) The Cloud Experts are not available to provide guidance for the Terminal Doctors on diagnosis and treatment at all times and in all settings. (3) In clinical trials, the main researchers are not available to monitor the research or guide the team at all times and in all settings. (4) Due to the lack of real-time quality control at all times and in all settings, non-standard diagnosis and treatment, with the features of a handicraft workshop, still exist to a considerable degree. The real cause lies in the limitations of the Internet technology itself, which cannot facilitate communication at all times and in all settings between the Cloud Experts and the Terminal Doctors involved in graded diagnosis and treatment. Therefore, the MIoT-based digital platforms need to be further improved, especially concerning the communication and interactions between humans and computers, and the integration and linkage between the virtual and real worlds. It is gratifying that the concept of the metaverse has been introduced, which provides a possible solution to all these problems, and serves as a foundation for the proposal and development of the Metaverse in Medicine.

With the rapid development of telemedicine equipment and information communication technology, telemedicine has developed rapidly and is used widely around the world as a new mode of medical service. This new technology has been used widely in China and has benefited a large number of patients. Due to the hospital-centric structure in health sector, resources and patients became increasingly concentrated in hospitals instead of primary care. In this way, telemedicine is a crucial method for government to the inequality of medical resources between urban and rural areas. But little is known about the influence of telemedicine on public primary hospitals in China. The objective of this study is to review the influence of telemedicine on capacity development of respiratory department in public primary hospital in China. A scoping review was conducted using electronic databases including PubMed, Cochrane Library, EMBASE and Google Scholar. Telemedicine has a major impact on the establishment of a complete national health system. The immediate sharing of medical information effectively alleviates the situation of serious information imbalance between doctors and patients. It also guides the public to make rational choice of medical behaviour. In public emergencies, telemedicine can quickly concentrate all kinds of high-quality medical resources to the sites, ensure the safety of people's lives, and provide effective rescue and treatment for the wounded in various special environments. It is conducive to giving full play to the market competition value of public hospital reputation, encouraging hospitals to continuously improve medical technology level, improving medical service quality, actively taking social medical and health responsibility, and this could promote the overall medical and health capacities development.

Background

Early diagnosis and treatment are key to improving survival and prognosis of patients with lung cancer. Liquid biopsy and artificial intelligence (AI) can help diagnose early lung cancer.

Case presentation

We present a 68-year-old female with a family history of pulmonary nodules without smoking history who found multiple nodules in the lungs on physical examination. Malignant lung nodules were diagnosed based on AI evaluation and 341 circulating abnormal cells (CACs). Surgical resection confirmed the diagnosis of pulmonary adenocarcinoma and the CACs decreased to 151 at postoperative follow-up in one month and to 54 six months after surgery.

Conclusion

CACs helps to improve the accuracy of AI diagnosis of early lung cancer and the prognosis of patients with lung cancer at follow-up.

Background

Digital mental healthcare interventions (DMHIs) have been repeatedly mentioned as a possible solution for the growing demand for accessible treatment for patients suffering from common mental health problems, i.e. depression and anxiety disorders. However, structural implementation of DMHI is sparse and results on outcome seems inconclusive. To enrich the body of evidence, this paper compares a need-driven digital mental healthcare intervention (DMHI) for patients diagnosed with depression or anxiety disorders with traditional face-to-face treatment. The digital treatment is provided using a smartphone app which provides videoconferencing, chat, calendar- and registration functions.

Method

In a naturalistic retrospective cohort study patients who received DMHI are compared to patients who received traditional face-to-face treatment. Furthermore three illustrative cases were selected to demonstrate how personalization is expressed in individual treatments.

Results

The first results of the DMHI compare favorably with traditional face-to-face treatment, showing comparable satisfaction rates, equal effectiveness, and a significant decrease in treatment duration in weeks.

Conclusion

The DMHI has the potential to be as effective, but more efficient than traditional face-to-face treatment. Furthermore the digital treatment opens up options to fine-tune the frequency, duration, and content of care contacts to align with patients' individual situations and personal preferences.

Bipolar disorder (BD) is a complex and severe mental illness with high mortality and relapse rates. Psychoeducational interventions based on scientific evidence could increase treatment adherence rates through a better comprehension of the illness. The aim of this study is to investigate the efficacy of a digital intervention using a mobile phone application as adjunctive treatment for BD. The study has been conducted since March 2019 and is divided in three phases: (1) mobile application development process and assessment, (2) pilot trial, and (3) evaluation and controlled trial. During the first phase MyBee app was developed with the following axes: general information about BD and its course, BD comorbidities and available treatments, lifestyle, sleep quality, diet, suicide and stigma, stress management, and relaxation exercises based on mindfulness techniques. The second phase was the 12-week long pilot trial, which used a quasi-experimental design and aimed to evaluate both the content of the digital intervention and the functionality of the MyBee app. Following, the controlled trial was conducted to compare the digital intervention through a mobile phone application as adjunctive treatment for BD, with a control group without intervention over a period of 12 weeks. Online-based strategies through mobile applications have been an important strategy to monitor symptoms, offer self-management, improve treatment adherence, and prevent relapse among BD patients.

The differential diagnosis between pulmonary tuberculous nodules and solid lung cancer nodules is difficult and easy to be misdiagnosed in clinic. The data of clinic and image features of Chest CT with 70 cases of non-calcified pulmonary tuberculous nodules and 198 cases of solid lung cancer nodules confirmed by pathology in the Department of Thoracic Surgery or Respiratory and Critical Care Medicine, the First Affiliated Hospital of Chongqing Medical University from January to September 2020 were collected retrospectively. The characteristics of clinical and chest CT were compared between pulmonary tuberculous nodules and solid lung cancer nodules. The sensitivity, specificity, accuracy and negative predictive value in the two groups were compared between Artificial Intelligence assisted diagnosis system and manual image reading. The results found that the mean age, past tumor history, family history of tumor, CT image features of nodules includes mean diameter, short burr, blood vessel crossing in the pulmonary tuberculous nodules group were lower than those in the solid lung cancer group (p < 0.05). In 35 cases of pulmonary tuberculous nodules group and 63 cases of solid lung cancer nodules group with Dicom format thin-slice chest CT, the sensitivity of AI-assisted diagnosis was 98.98 %. The diagnosis specificity, accuracy and negative predictive value in the AI group (80.61 %, 92.06 %, 60.00 %) were much higher than these in the intermediate respiratory physicians (62.24 %, 76.19 %, 37.14 %, p = 0.004, 0.015, 0.044) respectively, and there was no significant difference between AI and senior radiologists. There are many similarities in clinical and CT image features between pulmonary tuberculous nodules and solid lung cancer nodules. The ability of AI-assisted diagnosis system is better than that of intermediate physicians, reaching the diagnostic level of senior physicians, which is conducive to homogenization and improvement of the differential diagnosis ability of physicians.

The metaverse has entered people's horizons through virtual reality, digital twinning, the Internet of Things, blockchain technology, etc. In the current healthcare system, the management of chronic diseases, such as chronic obstructive pulmonary disease (COPD) and obstructive sleep apnea-hypopnea syndrome (OSAHS), still faces challenges, such as uneven distribution of medical resources, and difficulty in follow-up, overburdening of specialists, and so on. However, metaverse medical platforms incorporating advanced AI technologies, such as industrial-scale digital twins, may address these issues. In this article, we discuss the application prospect of these technologies in digital medicine and the future of the medical metaverse.