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Your LHC Olympics 2020: An online community Concern for Abnormality Recognition throughout High Vitality Science.
In order to solve the problem of low accuracy, high cost, and difficult detection of traditional algorithms, a new algorithm based on ultrasound imaging is proposed in this paper. The algorithm is based on fuzzy clustering to diagnose the disease and effectively improve the accuracy of the algorithm. By testing the actual scene, it effectively proves the effectiveness and accuracy of the algorithm, which can find and treat diseases in time and can be widely used and popularized in clinical research in China.The present work demonstrates the design and implementation of a human-safe, portable, noninvasive device capable of predicting type 2 diabetes, using electrical bioimpedance and biometric features to train an artificial learning machine using an active learning algorithm based on population selection. GPCR antagonist In addition, there is an API with a graphical interface that allows the prediction and storage of data when the characteristics of the person are sent. The results obtained show an accuracy higher than 90% with statistical significance (p  less then  0.05). The Kappa coefficient values were higher than 0.9, showing that the device has a good predictive capacity which would allow the screening process of type 2 diabetes. This development contributes to preventive medicine and makes it possible to determine at a low cost, comfortably, without medical preparation, and in less than 2 minutes whether a person has type 2 diabetes.
Specification of possible stress factors destabilizing the fibula stable osteosynthesis by the intramedullary nail with distal blocking and elastic fixation of distal syndesmosis by the thread with endobuttons by mathematical modelling of distal unstable ankle injuries.
. We studied the thread tension during the combined stable-elastic fixation of unstable injuries of the ankle joint in cross-syndesmosis fractures of the fibula (B, C Danis-Weber classification), which includes a one-time stable minimally invasive fixation with the intramedullary nail and elastic fixation by the thread with endobuttons. We used a titanium alloy for the intramedullary nail and polyester for the thread. The deformed state was studied using the methods of mechanics.

A model of a fractured fibula blocked with the intramedullary nail and fixed with the elastic thread was developed. A formulation to specify the rational tension forces of the elastic thread depending on the parameters of the fibula and intramedullary blocking nail and on the location of the bone injury was obtained. The effect of foot rotation on the thread tension was investigated. The results of theoretical research should be implemented in medical practice.

A mathematical model of the damaged fibula blocked by the intramedullary nail and fixed with the elastic thread was developed. Dependences for calculation of tension of the fixing thread were obtained. link2 A slight increase in thread tension during foot rotation was found.
A mathematical model of the damaged fibula blocked by the intramedullary nail and fixed with the elastic thread was developed. Dependences for calculation of tension of the fixing thread were obtained. A slight increase in thread tension during foot rotation was found.As the standard of life has increased with the advancement of the time, there has been an increasing stress on healthcare with the aging diet, and pressure sores occur in elderly hospitalized subjects. Of course, the emergence of related medical devices, especially auxiliary foam dressings, is constantly improving. Pressure ulcers are extremely harmful to the elderly. The use of virtual reality technology to simulate the treatment of foam excipients is to test the role of medical devices in virtual reality. In particular, the use of foam dressings in the management of pressure deposits is the most relevant study for this paper, which reviews the relevant literature and conducts a thematic study on patients in a specific urban hospital. The relevant materials were designed, the experiments were designed, and the relevant research data were obtained. Studies show that virtual reality-based preventive medical devices can improve the efficiency of pressure ulcer treatment in hospitals by about 12%. Pressure ulcers have different incidences among people of different ages. The probability is much higher than that of adolescents. Foam dressing is very effective in preventing pressure ulcers. The probability of pressure ulcers after using foam dressing is about 35% lower than that when it is not used.The application value of image mosaic algorithm (IMA) based CT imaging technology in the analysis of pathological characteristics of gastric polyp (GP) patients was explored in this work. link3 588 cases of GP patients in the hospital were selected as the research objects, and CT images based on IMA were adopted for examination. The patient's basic information, image performance, and gastroscopy results were recorded. The results showed that the absolute mean bright error (AMBE) index and information entropy of the IMA are 0.0625 and 7.0385, respectively. The clinical symptoms of patients were mostly abdominal pain (21.4%), abdominal distension (15.6%), and sour regurgitation (17.8%). The common size of GP was no more than 0.5 cm, and the common type was Yamada type II. There were notable differences between single and multiple GPs of different pathological types (P less then 0.05). Proliferative polyps were mostly found in the stomach and antrum, while fundus gland polyps were mostly in the stomach and fundus. There was significant difference between the growth location of the hyperplastic polyp and basal gland polyp (P less then 0.05). In summary, the CT images of IMA proposed in this paper can not only realize image splicing effectively but also were superior to the traditional SIFT method in the quality of splicing image and were conducive to the analysis of the pathological characteristics of GP patients, which had significant clinical promotion value.
To investigate the application value of a deep convolutional neural network (CNN) model for cytological assessment of thyroid nodules.

117 patients with thyroid nodules who underwent thyroid cytology examination in the Affiliated People's Hospital of Ningbo University between January 2017 and December 2019 were included in this study. 100 papillary thyroid cancer samples and 100 nonmalignant samples were collected respectively. The sample images were translated vertically and horizontally. Thus, 900 images were separately created in the vertical and horizontal directions. The sample images were randomly divided into training samples (
 = 1260) and test samples (
 = 540) at the ratio of 7  3 per the training sample to test sample. According to the training samples, the pretrained deep convolutional neural network architecture Resnet50 was trained and fine-tuned. A convolutional neural network-based computer-aided detection (CNN-CAD) system was constructed to perform full-length scan of the test sample sl can be used for the cytological diagnosis of malignant thyroid tumor in the clinic.
A CNN model exhibits a high value in the cytological diagnosis of thyroid diseases which can be used for the cytological diagnosis of malignant thyroid tumor in the clinic.
We aimed to evaluate whether circulating tumor cells (CTCs) were the prognostic indicator responsible for chemotherapy and survival of NSCLC patients.

Between January 2013 and September 2017, CTCs in the peripheral blood of histologically confirmed stages III and IV NSCLC patients were collected. Blood specimens were obtained on the first day of treatment, chemotherapy 2 and 4 cycles, or targeted therapy 1 and 2 months for CTCs detection. The positive CTC status was defined as one or more CTCs per 7.5 ml.

100 patients were enrolled, of which 48 patients (48%) were identified to be CTC positive at baseline. A higher CTC-positive rate was observed in stage IV NSCLC patients than stage III patients (69% vs. 40%,
=0.015). CTC cluster was significantly correlated with disease control rate. Based on the baseline CTC number, patients were divided into low CTC levels (<4 CTCs, LL) and high CTC levels (≥4 CTCs, HL). There was clinically significant shorter median OS and OS (overall survival) and PFS (progression-free survival) in HL group patients (
< 0.001).

The positive association between the CTC number and survival suggested that the baseline CTC number and changes during treatment might be the prognostic information of response rate and overall survival in Chinese patients suffering stage III/IV NSCLC.
The positive association between the CTC number and survival suggested that the baseline CTC number and changes during treatment might be the prognostic information of response rate and overall survival in Chinese patients suffering stage III/IV NSCLC.Internet of things technology began to spread to all industries of our lives; the application of medical internet of things in many hospitals highlighted its advantages and brought a lot of convenience to patients and medical staff. With the continuous progress of China's medical reform and the continuous improvement of patients' requirements for medical service quality, this paper discusses the application of medical internet of things in clinical nursing in ward, and the basic information collection, infusion, and mobile nursing were discussed and studied. Through the parallel control study of the laboratory itself, this paper evaluates whether the two different clinical measurement methods of medical internet of things technology and traditional technology are consistent in body temperature, pulse, respiration, and blood oxygen saturation. At the same time, it also deeply studies the value and advantages of internet of things technology in the application of other monitoring indicators in clinical nursing and analyses the problems in its application. The experimental data show that the two measurement methods with different principles can be completely replaced in clinical application, and the time efficiency of the new clinical nursing method under the medical internet of things technology in mapping body temperature, pulse, and respiration has been improved by 76.20% and 72.02%, respectively, surpassing the traditional information technology and realizing the intelligent, automatic, and standardized data acquisition method. It ensures the authenticity of data and the real-time of information flow and meets the needs of resource sharing and medical regional interconnection.The Brain-Computer Interface (BCI) permits persons with impairments to interact with the real world without using the neuromuscular pathways. BCIs are based on artificial intelligence piloted systems. They collect brain activity patterns linked to the mental process and transform them into commands for actuators. The potential application of BCI systems is in the rehabilitation centres. In this context, a novel method is devised for automated identification of the Motor Imagery (MI) tasks. The contribution is an effective hybridization of the Multiscale Principal Component Analysis (MSPCA), Wavelet Packet Decomposition (WPD), statistical features extraction from subbands, and ensemble learning-based classifiers for categorization of the MI tasks. The intended electroencephalogram (EEG) signals are segmented and denoised. The denoising is achieved with a Daubechies algorithm-based wavelet transform (WT) incorporated in the MSPCA. The WT with the 5th level of decomposition is used. Onward, the Wavelet Packet Decomposition (WPD), with the 4th level of decomposition, is used for subbands formation.
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