Technology and Health Care - Volume 30, issue S1

Authors: Wang, Xingang | Shao, Cuiling | Liu, Wensheng | Liang, Hu | Li, Na

Article Type: Research Article

Abstract: BACKGROUND: HER2 gene expression is one of the main reference indicators for breast cancer detection and treatment, and it is also an important target for tumor targeted therapy drug selection. Therefore, the correct detection and evaluation of HER2 gene expression has important value for clinical treatment of breast cancer. OBJECTIVE: The study goal is to better classify HER2 images. METHODS: For general convolution neural network, with the increase of network layers, over fitting phenomenon is often very serious, which requires setting the value of random descent ratio, and parameter adjustment is often time-consuming …and laborious, so this paper uses residual network, with the increase of network layer, the accuracy will not be reduced. RESULTS: In this paper, a HER2 image classification algorithm based on improved residual network is proposed. Experimental results show that the proposed HER2 network has high accuracy in breast cancer assessment. Conclusion: Taking HER2 images in Stanford University database as experimental data, the accuracy of HER2 image automatic classification is improved through experiments. This method will help to reduce the detection intensity and improve the accuracy of HER2 image classification. Show more

Keywords: Breast cancer, HER2, deep neural network, classification, residual network

DOI: 10.3233/THC-228020

Citation: Technology and Health Care, vol. 30, no. S1, pp. 215-224, 2022

Authors: Wang, Hao | Sun, Bin | Li, Xiayuan | Wang, Yun | Yang, Zhengping

Article Type: Research Article

Abstract: BACKGROUND: Patients with unexplained pneumonia appeared in Wuhan, Hubei Province at the end of 2019. OBJECTIVE: To analyze the clinical data of patients with severe COVID-19. METHODS: Medical records of 28 severe patients admitted to the intensive care unit of Wuhan Xinzhou District People’s Hospital were collected from January 31 to March 17. RESULTS: The mortality rate of severe patients in our study was 39.3%. There were statistically significant differences in age, admission systolic blood pressure, lymphocyte count, albumin, total bilirubin, and lactate dehydrogenase between the death group and the …survival group (P < 0.05). There were statistically significant differences in APACHE II, CURB-65, SOFA, respiratory frequency, systolic pressure, platelet, procalcitonin, albumin, creatinine, creatine kinase isoenzyme, lactate dehydrogenase, chloride ion, prothrombin time, international normalized ratio, arterial partial pressure of oxygen, and FiO2 at ICU between the death group and the survival group (P < 0.05). CONCLUSIONS: Fever and cough are the main symptoms, which is useful for predicting the prognosis to dynamically measure the APACHE II, CURB-65, SOFA, respiratory frequency, lymphocyte count, platelet, lactate dehydrogenase, and coagulation tests. The drugs that protect the liver and heart may improve the survival rate of patients with severe COVID-19. Show more

Keywords: Coronavirus disease 2019, critical illness, prognosis

DOI: 10.3233/THC-228021

Citation: Technology and Health Care, vol. 30, no. S1, pp. 225-234, 2022

Authors: Du, Mengqing | Qiu, Qian | Hao, Dongmei | Zhou, Xiya | Yang, Lin | Liu, Xiaohong

Article Type: Research Article

Abstract: BACKGROUND: As an essential indicator of labour and delivery, uterine contraction (UC) can be detected by manual palpation, external tocodynamometry and internal uterine pressure catheter. However, these methods are not applicable for long-term monitoring. OBJECTIVE: This paper aims to recognize UCs with electrohysterogram (EHG) and find the best electrode combination with fewer electrodes. METHODS: 112 EHG recordings were collected by our bespoke device in our study. Thirteen features were extracted from EHG segments of UC and non-UC. Four classifiers of the decision tree, support vector machine (SVM), artificial neural network, and convolutional neural …network were established to identify UCs. The optimal classifier among them was determined by comparing their classification results. The optimal classifier was applied to evaluate all the possible electrode combinations with one to eight electrodes. RESULTS: The results showed that SVM achieved the best classification capability. With SVM, the combination of electrodes on the right part of the uterine fundus and around the uterine body’s median axis achieved the overall best performance. CONCLUSIONS: The optimal electrode combination with fewer electrodes was confirmed to improve the clinical application for long-term monitoring of UCs. Show more

Keywords: Electrode combination, uterine contraction, electrohysterogram (EHG), classifier

DOI: 10.3233/THC-228022

Citation: Technology and Health Care, vol. 30, no. S1, pp. 235-242, 2022

Authors: Ryu, Seonho | Ryu, Jaemyung | Choi, Hojong

Article Type: Research Article

Abstract: BACKGROUND: Compared to benchtop ultrasound machines, mobile ultrasound machines require portable batteries when acquiring information regarding human tissues during outdoor activities. OBJECTIVE: A novel fisheye lens type was designed to address the charging issue where it is difficult to constantly track the sun. This method does not require the use of a mechanical motor that constantly tracks the sun to charge the portable batteries. METHODS: To obtain an optical solar power system, the numerical aperture (NA) and field angle must be increased. Therefore, we use the fisheye lens with the largest field angle. …RESULTS: The NA of the designed fisheye lens system reaches 0.75, allowing light collection of approximately ± 48 ∘ . Additionally, the efficiency ratio of the central and surrounding areas also satisfies more than 80% at a field angle of 85 ∘ and more than 70% at field angles of 85 ∘ to 90 ∘ , respectively. CONCLUSIONS: We designed a novel fisheye lens for solar-powered mobile ultrasound machines used outdoors. Show more

Keywords: Mobile ultrasound machines, fisheye lens, solar power

DOI: 10.3233/THC-228023

Citation: Technology and Health Care, vol. 30, no. S1, pp. 243-250, 2022

Authors: Park, Chanhee | An, Yeongsang | Yoon, Hyunsik | Park, Ilbong | Kim, Kyoungtae | Kim, Chungyoo | Cha, Youngjoo

Article Type: Research Article

Abstract: BACKGROUND: Although patients with frozen shoulders have the range of motion (ROM) of their shoulder’s abduction movements measured at hospital and the physical therapy visits, multiple visits to check for progress is often difficult. Thus, we developed an artificial intelligence-based image recognition detectable sensor (AIRDS) intended for easy use at home. OBJECTIVE: The purpose of this study was to determine the accuracy of a sensor (AIRDS) measuring shoulder abduction angle, thus offering a valid and feasible system for monitoring patients with frozen shoulder. METHODS: Ten patients with frozen shoulder (5 males, 5 females) …performed shoulder joint movements while being measured with the AIRDS system and the 3-dimensional Vicon system. The measure of the outcome included the linear regression of the shoulder abduction joint kinematics. RESULTS: Linear regression analysis of the AIRDS system and the Vicon system demonstrated a significant correlation coefficient of R 2 = 0.9979 (P < 0.05). CONCLUSIONS: Our results provide novel, promising evidence that AIRDS can accurately measure the timing and total spatial characteristics of clinical movements. AIRDS is designed to provide real-time ROM measurements for joint mobility using artificial intelligence instead of the judgement of the physical therapist. Show more

Keywords: Shoulder abduction, convolutional neural network, artificial intelligence, frozen shoulder

DOI: 10.3233/THC-228024

Citation: Technology and Health Care, vol. 30, no. S1, pp. 251-257, 2022

Authors: Hao, Peiyu | Chen, Limei | Ge, Yuxi | You, Yaqian | Yan, Gen | Jin, Zhe-Wu

Article Type: Research Article

Abstract: BACKGROUND: Brain metastasis (BM) is one of the main causes of high morbidity and mortality in cancer patients. OBJECTIVE: To evaluate the factors that influenced the survival time of patients with primary cancer and survival time after BM. METHODS: Ninety patients with BM diagnosed by magnetic resonance imaging (MRI) were included in the study. We retrospectively analyzed the time to brain metastasis (TTB), overall survival time (OS1) and survival time after BM (OS2). The Kaplan-Meier method and Cox regression analysis were used for survival analyses. RESULTS: The median TTB was …12.0 (95% CI : 9.2–14.8 months), the median OS1 was 31.0 (95% CI : 25.8–35.2 months) and the median OS2 was 14.0 (95% CI : 10.9–17.1 months). Surgical excision of the primary tumor was an independent factor for a prolonged TTB (p < 0.000) and prolonged OS1 (p < 0.000). A single intracranial metastatic lesion was an independent protective factor for prolonged OS1 (p = 0.011) and prolonged OS2 (p = 0.050). TTB, OS1 and OS2 were analyzed with Gender (p < 0.000, < 0.000, and = 0.017, respectively). CONCLUSIONS: It suggests that TTB can be prolonged by primary tumor resection. Furthermore, women with a prolonged TTB and single intracranial metastasis are associated with high OS. These were helpful for the clinical treatment of BM patients before brain metastasis. Show more

Keywords: Primary tumor, brain metastasis, time to brain metastasis, overall survival, retrospective analysis, surgery

DOI: 10.3233/THC-228025

Citation: Technology and Health Care, vol. 30, no. S1, pp. 259-270, 2022

Authors: Hu, Junwei | Yan, Zhuangzhi | Jiang, Jiehui

Article Type: Research Article

Abstract: BACKGROUND: Tongue inspection is vital in traditional Chinese medicine. Fissured tongue is an important feature in tongue diagnosis, and primarily corresponds to three Chinese medicine syndromes: syndrome-related hotness, blood deficiency, and insufficiency of the spleen. Diagnosis of the syndrome is significantly affected by the experience of clinicians, and it is difficult for young doctors to perform accurate diagnoses. OBJECTIVE: The syndrome not only depends on the local features based on fissured regions but also on the global features of the whole tongue; therefore, a syndrome diagnosis framework combining the global and local features of a fissured …tongue image was developed in the present study to achieve a quantitative and objective diagnosis. METHODS: First, we detected the fissured region of a tongue image using a single-shot multibox detector. Second, we extracted the global and local features from a whole tongue image and a fissured region using TongueNet (developed in-house). Third, we developed a classifier to determine the final syndrome. RESULTS: Based on an experiment involving 721 fissured tongue images, we discovered that TongueNet affords better feature extraction. The accuracy of TongueNet was 4% (p < 0.05) and 3% (p < 0.05) higher than that of InceptionV3 and ResNet18, respectively, for whole tongue images. Meanwhile, at local fissured regions, the accuracy of TongueNet was 3% (p < 0.05) higher than that of InceptionV3 and equal to that of ResNet18. Finally, the fusion features outperformed the global and local features with a 78% accuracy. CONCLUSIONS: Our findings indicate that TongueNet designed with batch normalization and dropout is more suitable for uncomplicated images than InceptionV3 and ResNet18. In addition, compared with the global features, the fusion features supplement the detailed information of the fissures and improve classification accuracy. Show more

Keywords: Chinese medicine syndrome, fissured tongue, convolutional neural network

DOI: 10.3233/THC-228026

Citation: Technology and Health Care, vol. 30, no. S1, pp. 271-283, 2022

Authors: Lu, Jiayu | Jiang, Hongqing | Zhang, Song | Yang, Yimin | Hao, Dongmei | Li, Xuwen | Chen, Aiqing | Shao, Jing | Liu, Xiaohong | Yang, Lin

Article Type: Research Article

Abstract: BACKGROUND: Gestational diabetes mellitus (GDM) is a metabolic disease that seriously endangers the health of mothers and children. It is important to monitor GDM in real-time before diagnosis and to prevent it effectively. OBJECTIVE: GDM was divided into the second trimester diagnosed diabetes mellitus (GDM_24) and the third trimester diagnosed diabetes mellitus (GDM_30). The risk prediction of two types of GDM was performed in normal pregnant women at 11–13 and 16–19 weeks of pregnancy, respectively. METHODS: By stages, the K-W test was used to analyze the differences between basic information and energy metabolism …factors, and multiple logistic regression was used to analyze the risk of energy metabolism factors and to correct the confounders with significant differences. RESULTS: For the GDM_24 group, each additional unit of oxygen consumption (VO 2 ), carbon dioxide production, and resting energy expenditure (REE) increased the risk by 2.4%, 3.5%, 0.4%, and 2.1%, 2.6%, and 0.3%, respectively, at 11–13 and 16–19 weeks of pregnancy. For the GDM_30 group, each additional unit of VO 2 and REE was associated with an increased risk of 2.3% and 0.3%, respectively, at 16–19 weeks of pregnancy. CONCLUSION: The risk of GDM_30 only appeared in pregnant women during 16–19 weeks of pregnancy, which may indicate that GDM_24 and GDM_30 have different pathogenesis. Show more

Keywords: Diabetes mellitus in the second trimester, diagnosis of diabetes mellitus in the third trimester, energy metabolism

DOI: 10.3233/THC-THC228027

Citation: Technology and Health Care, vol. 30, no. S1, pp. 285-292, 2022

Authors: Cao, Difei | Xue, Jiaying | Huang, Guoqing | An, Jing | An, Weiwei

Article Type: Research Article

Abstract: BACKGROUND: Alternative splicing is a mechanism to produce different proteins with diverse functions from one gene. Many splicing factors play an important role in cancer progression. PRPF8 is a core protein component of the spliceosome complex, U4/U6-U5 tri-snRNP. OBJECTIVE: However, PRPF8 involved in mRNA alternative splicing are rarely included in the prognosis. METHODS: We found that PRPF8 was expressed in all examined cancer types. Further analyses found that PRPF8 expression was significantly different between the breast cancer and paracancerous tissues. RESULTS: Survival analyses showed that PRPF8 …-high patients had a poor prognosis, and the expression of PRPF8 is associated with distant metastasis-free survival (DMFS) and post progression survival (PPS). Gene Set Enrichment Analysis (GSEA) has revealed that PRPF8 expression is correlated with TGF-β , JAK-STAT, and cell cycle control pathways. Consistent with these results, upon PRPF8 silencing, the growth of MCF-7 cells was reduced, the ability of cell clone formation was weakened, and p ⁢ 21 expression was increased. CONCLUSIONS: These results have revealed that PRPF8 is a significant factor for splicing in breast cancer progression. Show more

Keywords: PRPF8, breast cancer, alternative splicing, prognosis

DOI: 10.3233/THC-THC228028

Citation: Technology and Health Care, vol. 30, no. S1, pp. 293-301, 2022

Authors: Li, Yingzhi | Xiao, Laiyuan

Article Type: Research Article

Abstract: BACKGROUND: With the continuous expansion of urban scale and the increasing concentration of population, public health crisis has become an important part of urban residents’ health management. The outbreak of the COVID-19 pandemic in Wuhan in 2020 has sounded the alarm. OBJECTIVE: With the government at all levels to carry out the construction of urban Internet of things and information internet, the Internet backbone network has been built, deployed a large number of sensors, and collected a large number of urban situation data. METHODS: In this paper, situational awareness technology is introduced into …public health emergency services. RESULTS: By constructing ontology, situational data and residents’ health data are integrated. Through key technologies such as situational data collection, data fusion and data mining, real-time perception of environmental conditions of public health emergency scene is realized, and situational data fusion and situational information reasoning model are constructed. CONCLUSIONS: The model is applied to the public health crisis emergency simulation system to verify the effectiveness of the model. Show more

Keywords: Situational awareness, ontology technology, public health emergency

DOI: 10.3233/THC-THC228029

Citation: Technology and Health Care, vol. 30, no. S1, pp. 303-314, 2022