With the rise of mobile medicine, the development of new technologies such as smart sensing, and the popularization of personalized health concepts, the field of smart wearable devices has developed ...rapidly in recent years. Among them, medical wearable devices have become one of the most promising fields. These intelligent devices not only assist people in pursuing a healthier lifestyle but also provide a constant stream of health care data for disease diagnosis and treatment by actively recording physiological parameters and tracking metabolic status. Therefore, wearable medical devices have the potential to become a mainstay of the future mobile medical market.
Although previous reviews have discussed consumer trends in wearable electronics and the application of wearable technology in recreational and sporting activities, data on broad clinical usefulness are lacking. We aimed to review the current application of wearable devices in health care while highlighting shortcomings for further research. In addition to daily health and safety monitoring, the focus of our work was mainly on the use of wearable devices in clinical practice.
We conducted a narrative review of the use of wearable devices in health care settings by searching papers in PubMed, EMBASE, Scopus, and the Cochrane Library published since October 2015. Potentially relevant papers were then compared to determine their relevance and reviewed independently for inclusion.
A total of 82 relevant papers drawn from 960 papers on the subject of wearable devices in health care settings were qualitatively analyzed, and the information was synthesized. Our review shows that the wearable medical devices developed so far have been designed for use on all parts of the human body, including the head, limbs, and torso. These devices can be classified into 4 application areas: (1) health and safety monitoring, (2) chronic disease management, (3) disease diagnosis and treatment, and (4) rehabilitation. However, the wearable medical device industry currently faces several important limitations that prevent further use of wearable technology in medical practice, such as difficulties in achieving user-friendly solutions, security and privacy concerns, the lack of industry standards, and various technical bottlenecks.
We predict that with the development of science and technology and the popularization of personalized health concepts, wearable devices will play a greater role in the field of health care and become better integrated into people's daily lives. However, more research is needed to explore further applications of wearable devices in the medical field. We hope that this review can provide a useful reference for the development of wearable medical devices.
Background
As a distributed technology, blockchain has attracted increasing attention from stakeholders in the medical industry. Although previous studies have analyzed blockchain applications from ...the perspectives of technology, business, or patient care, few studies have focused on actual use-case scenarios of blockchain in health care. In particular, the outbreak of COVID-19 has led to some new ideas for the application of blockchain in medical practice.
Objective
This paper aims to provide a systematic review of the current and projected uses of blockchain technology in health care, as well as directions for future research. In addition to the framework structure of blockchain and application scenarios, its integration with other emerging technologies in health care is discussed.
Methods
We searched databases such as PubMed, EMBASE, Scopus, IEEE, and Springer using a combination of terms related to blockchain and health care. Potentially relevant papers were then compared to determine their relevance and reviewed independently for inclusion. Through a literature review, we summarize the key medical scenarios using blockchain technology.
Results
We found a total of 1647 relevant studies, 60 of which were unique studies that were included in this review. These studies report a variety of uses for blockchain and their emphasis differs. According to the different technical characteristics and application scenarios of blockchain, we summarize some medical scenarios closely related to blockchain from the perspective of technical classification. Moreover, potential challenges are mentioned, including the confidentiality of privacy, the efficiency of the system, security issues, and regulatory policy.
Conclusions
Blockchain technology can improve health care services in a decentralized, tamper-proof, transparent, and secure manner. With the development of this technology and its integration with other emerging technologies, blockchain has the potential to offer long-term benefits. Not only can it be a mechanism to secure electronic health records, but blockchain also provides a powerful tool that can empower users to control their own health data, enabling a foolproof health data history and establishing medical responsibility.
The phenotypic polarization of macrophages are involved in steroid-induced osteonecrosis (ON). This study tried to investigate the detrimental and beneficial roles of M1/M2 macrophages associated ...with TNF-a in ON. Mice ON model was induced by the injection of methylprednisolone. After that, flow cytometry technique, immunohistochemistry, immunofluorescence, ELISA, and RT-PCR methods were used to investigate the expression pattern of macrophages and the expression of inflammatory cytokines. During the progression of ON, massive chronic inflammatory cells infiltrated into the necrotic zone, represented by the infiltration of macrophages. In the early stage of ON, there was high TNF-a activity; and a large population of M1 macrophages infiltrated into the necrotic zone. On the contrary, the expression of TNF-a gradually decreased; simultaneously, a larger M2 cell population presented in the necrotic zone in the late stage of ON. The increased M2 macrophages could be beneficial for resolving inflammation and promoting tissue repair, confirmed by the histologic findings of appositional new bone formation around the necrotic bone. Thus, it showed that TNF-a-mediated alteration of M1/M2 macrophage polarization contributed to the pathogenesis of steroid-induced osteonecrosis. M1-polarized macrophages appeared to be disruptive in the early stage of ON, while M2-polarized macrophages played an important role in the late stage during the pathogenesis of ON.
In this paper, in view of the existing mechanical sand cleaning technology, circulating sand flushing technology, and negative pressure sand cleaning technology, which cannot establish circulation, ...the pump lift is limited, the sand cleaning efficiency is low, and many other problems when cleaning the sand in deep wells that are prone to leakage, a new type of sand cleaning system that can realize the local circulation and storage of sand fluid at the bottom of the well is designed. The critical problem to be solved in this design is how to simultaneously meet the dual requirements of local circulation and storage, that is, how to coordinate the contradiction between gravel carrying and settlement. Therefore, studying the mechanism of sand transport and settlement in the new type of sand cleaning cylinder is necessary. The discrete phase model of the sand liquid flowing in the sand cleaning cylinder was established using EDEM-FLUENT. The numerical simulation and analysis of the movement law of sand grains, the trajectory line clouds of sand grains, and the variation law of sand settling rate, sand mass flow rate, and sand-carrying liquid flow rate under different working parameters were obtained. The conclusion shows that when the mass flow rate of sand particles is 0.5–0.8 kg/s, and the flow rate of sand-carrying liquid is 0.5– 1 m/s, the grit removal effect of the sand cleaning cylinder is better. In order to verify the sand cleaning effect of this new sand cleaning system and the accuracy of the numerical analysis model, the ground simulation test platform of the sand cleaning cylinder was built, and simulated sand cleaning tests were carried out under different sand particle sizes and different sand-carrying fluid flow rates. The test results show that the new sand cleaning system clears sand well. Comparing the numerical simulation results with the experimental results, the two have the same variation pattern, which verifies the feasibility of this new sand cleaning system and the correctness of the numerical analysis model. The study provides a new sand cleaning system solution, which solves the problem that existing sand cleaning techniques cannot quickly and efficiently clean up sunken sand from leaking oil and gas wells and provides a basis for the selection of field operating parameters for the new sand cleaning system.
We explored a new artificial intelligence-assisted method to assist junior ultrasonographers in improving the diagnostic performance of uterine fibroids and further compared it with senior ...ultrasonographers to confirm the effectiveness and feasibility of the artificial intelligence method. In this retrospective study, we collected a total of 3870 ultrasound images from 667 patients with a mean age of 42.45 years ± 6.23 SD for those who received a pathologically confirmed diagnosis of uterine fibroids and 570 women with a mean age of 39.24 years ± 5.32 SD without uterine lesions from Shunde Hospital of Southern Medical University between 2015 and 2020. The DCNN model was trained and developed on the training dataset (2706 images) and internal validation dataset (676 images). To evaluate the performance of the model on the external validation dataset (488 images), we assessed the diagnostic performance of the DCNN with ultrasonographers possessing different levels of seniority. The DCNN model aided the junior ultrasonographers (Averaged) in diagnosing uterine fibroids with higher accuracy (94.72% vs. 86.63%, P < 0.001), sensitivity (92.82% vs. 83.21%, P = 0.001), specificity (97.05% vs. 90.80%, P = 0.009), positive predictive value (97.45% vs. 91.68%, P = 0.007), and negative predictive value (91.73% vs. 81.61%, P = 0.001) than they achieved alone. Their ability was comparable to that of senior ultrasonographers (Averaged) in terms of accuracy (94.72% vs. 95.24%, P = 0.66), sensitivity (92.82% vs. 93.66%, P = 0.73), specificity (97.05% vs. 97.16%, P = 0.79), positive predictive value (97.45% vs. 97.57%, P = 0.77), and negative predictive value (91.73% vs. 92.63%, P = 0.75). The DCNN-assisted strategy can considerably improve the uterine fibroid diagnosis performance of junior ultrasonographers to make them more comparable to senior ultrasonographers.
Background
The COVID-19 outbreak has now become a pandemic and has had a serious adverse impact on global public health. The effect of COVID-19 on the lungs can be determined through 2D computed ...tomography (CT) imaging, which requires a high level of spatial imagination on the part of the medical provider.
Objective
The purpose of this study is to determine whether viewing a 3D hologram with mixed reality techniques can improve medical professionals’ understanding of the pulmonary lesions caused by COVID-19.
Methods
The study involved 60 participants, including 20 radiologists, 20 surgeons, and 20 medical students. Each of the three groups was randomly divided into two groups, either the 2D CT group (n=30; mean age 29 years range 19-38 years; males=20) or the 3D holographic group (n=30; mean age 30 years range 20=38 years; males=20). The two groups completed the same task, which involved identifying lung lesions caused by COVID-19 for 6 cases using a 2D CT or 3D hologram. Finally, an independent radiology professor rated the participants' performance (out of 100). All participants in two groups completed a Likert scale questionnaire regarding the educational utility and efficiency of 3D holograms. The National Aeronautics and Space Administration Task Load Index (NASA-TLX) was completed by all participants.
Results
The mean task score of the 3D hologram group (mean 91.98, SD 2.45) was significantly higher than that of the 2D CT group (mean 74.09, SD 7.59; P<.001). With the help of 3D holograms, surgeons and medical students achieved the same score as radiologists and made obvious progress in identifying pulmonary lesions caused by COVID-19. The Likert scale questionnaire results showed that the 3D hologram group had superior results compared to the 2D CT group (teaching: 2D CT group median 2, IQR 1-2 versus 3D group median 5, IQR 5-5; P<.001; understanding and communicating: 2D CT group median 1, IQR 1-1 versus 3D group median 5, IQR 5-5; P<.001; increasing interest: 2D CT group median 2, IQR 2-2 versus 3D group median 5, IQR 5-5; P<.001; lowering the learning curve: 2D CT group median 2, IQR 1-2 versus 3D group median 4, IQR 4-5; P<.001; spatial awareness: 2D CT group median 2, IQR 1-2 versus 3D group median 5, IQR 5-5; P<.001; learning: 2D CT group median 3, IQR 2-3 versus 3D group median 5, IQR 5-5; P<.001). The 3D group scored significantly lower than the 2D CT group for the “mental,” “temporal,” “performance,” and “frustration” subscales on the NASA-TLX.
Conclusions
A 3D hologram with mixed reality techniques can be used to help medical professionals, especially medical students and newly hired doctors, better identify pulmonary lesions caused by COVID-19. It can be used in medical education to improve spatial awareness, increase interest, improve understandability, and lower the learning curve.
Trial Registration
Chinese Clinical Trial Registry ChiCTR2100045845; http://www.chictr.org.cn/showprojen.aspx?proj=125761
We aimed to compare the intraoperative and early postoperative clinical outcomes of using an acromioclavicular joint hook plate (AJHP) versus a locking plate (LP) in the treatment of anterior ...sternoclavicular joint dislocation.
Seventeen patients with anterior sternoclavicular joint dislocation were retrospectively analyzed from May 2014 to September 2019. Six patients were surgically treated with an AJHP, and 11 were surgically treated with an LP. Five male and one female patients composed the AJHP group, and nine male and two female patients composed the LP group. The mean age of all patients was 49.5 years.
Reduction and fixation were performed with AJHP or LP in all 17 patients. The mean operative blood loss, operative time, and length of incision in the AJHP group were significantly better than those in the LP group. Shoulder girdle movement of the AJHP group was significantly better than that of the LP group.
This study revealed that AJHP facilitated glenohumeral joint motion, reduced the risk of rupture of mediastinal structures, required a shorter incision, and had lesser blood loss and a shorter duration of operation compared with LP. However, some deficiencies require further improvement.
Objective:
To explore a new artificial intelligence (AI)-aided method to assist the clinical diagnosis of femoral intertrochanteric fracture (FIF), and further compare the performance with human ...level to confirm the effect and feasibility of the AI algorithm.
Methods:
700 X-rays of FIF were collected and labeled by two senior orthopedic physicians to set up the database, 643 for the training database and 57 for the test database. A Faster-RCNN algorithm was applied to be trained and detect the FIF on X-rays. The performance of the AI algorithm such as accuracy, sensitivity, miss diagnosis rate, specificity, misdiagnosis rate, and time consumption was calculated and compared with that of orthopedic attending physicians.
Results:
Compared with orthopedic attending physicians, the Faster-RCNN algorithm performed better in accuracy (0.88 vs. 0.84 ± 0.04), specificity (0.87 vs. 0.71 ± 0.08), misdiagnosis rate (0.13 vs. 0.29 ± 0.08), and time consumption (5 min vs. 18.20 ± 1.92 min). As for the sensitivity and missed diagnosis rate, there was no statistical difference between the AI and orthopedic attending physicians (0.89 vs. 0.87 ± 0.03 and 0.11 vs. 0.13 ± 0.03).
Conclusion:
The AI diagnostic algorithm is an available and effective method for the clinical diagnosis of FIF. It could serve as a satisfying clinical assistant for orthopedic physicians.
To develop and assess a deep convolutional neural network (DCNN) model for the automatic detection of bone metastases from lung cancer on computed tomography (CT).
In this retrospective study, CT ...scans acquired from a single institution from June 2012 to May 2022 were included. In total, 126 patients were assigned to a training cohort (n = 76), a validation cohort (n = 12), and a testing cohort (n = 38). We trained and developed a DCNN model based on positive scans with bone metastases and negative scans without bone metastases to detect and segment the bone metastases of lung cancer on CT. We evaluated the clinical efficacy of the DCNN model in an observer study with five board-certified radiologists and three junior radiologists. The receiver operator characteristic curve was used to assess the sensitivity and false positives of the detection performance; the intersection-over-union and dice coefficient were used to evaluate the segmentation performance of predicted lung cancer bone metastases.
The DCNN model achieved a detection sensitivity of 0.894, with 5.24 average false positives per case, and a segmentation dice coefficient of 0.856 in the testing cohort. Through the radiologists-DCNN model collaboration, the detection accuracy of the three junior radiologists improved from 0.617 to 0.879 and the sensitivity from 0.680 to 0.902. Furthermore, the mean interpretation time per case of the junior radiologists was reduced by 228 s (p = 0.045).
The proposed DCNN model for automatic lung cancer bone metastases detection can improve diagnostic efficiency and reduce the diagnosis time and workload of junior radiologists.
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