A robust method for VR-based hand gesture recognition using density-based CNN

Many VR-based medical purposes applications have been developed to help patients with mobility decrease caused by accidents, diseases, or other injuries to do physical treatment efficiently. VR-based applications were considered more effective helper for individual physical treatment because of their lowcost equipment and flexibility in time and space, less assistance of a physical therapist. A challenge in developing a VR-based physical treatment was understanding the body part movement accurately and quickly. We proposed a robust pipeline to understanding hand motion accurately. We retrieved our data from movement sensors such as HTC vive and leap motion. Given a sequence position of palm, we represent our data as binary 2D images of gesture shape. Our dataset consisted of 14 kinds of hand gestures recommended by a physiotherapist. Given 33 3D points that were mapped into binary images as input, we trained our proposed density-based CNN. Our CNN model concerned with our input characteristics, having many blank block pixels, single-pixel thickness shape and generated as a binary image. Pyramid kernel size applied on the feature extraction part and classification layer using softmax as loss function, have given 97.7% accuracy

A robust method for VR-based hand gesture recognition using density-based CNN

Many VR-based medical purposes applications have been developed to help patients with mobility decrease caused by accidents, diseases, or other injuries to do physical treatment efficiently. VR-based applications were considered more effective helper for individual physical treatment because of their low-cost equipment and flexibility in time and space, less assistance of a physical therapist. A challenge in developing a VR-based physical treatment was understanding the body part movement accurately and quickly. We proposed a robust pipeline to understanding hand motion accurately. We retrieved our data from movement sensors such as HTC vive and leap motion. Given a sequence position of palm, we represent our data as binary 2D images of gesture shape. Our dataset consisted of 14 kinds of hand gestures recommended by a physiotherapist. Given 33 3D points that were mapped into binary images as input, we trained our proposed density-based CNN. Our CNN model concerned with our input characteristics, having many 'blank block pixels', 'single-pixel thickness' shape and generated as a binary image. Pyramid kernel size applied on the feature extraction part and classification layer using softmax as loss function, have given 97.7% accuracy

Relationship Between Snoring Intensity and Severity of Obstructive Sleep Apnea

ObjectivesThe aim of this study was to determine the relationship between the intensity of snoring and severity of sleep apnea using Watch-PAT (peripheral arterial tone) 100.MethodsA total of 404 patients (338 males and 66 females) who underwent home-based portable sleep study using Watch-PAT 100 for obstructive sleep apnea (OSA) from January 2009 through December 2011 were included in this study. Subjects were divided into 4 groups; no OSA (PAT apnea hypopnea index [pAHI]<5/hour), mild OSA (5≤pAHI<15/hour), moderate OSA (15≤pAHI<30/hour), or severe OSA groups (pAHI≥30/hour). Mean snoring intensity and percent sleep time with snoring intensity greater than 40, 50, and 60 dB were measured by Watch-PAT 100. Correlations of these parameters with apnea hypopnea index (AHI), respiratory disturbance index (RDI), and oxygen desaturation index were assessed.ResultsThe mean age and body mass index were 46.5±14.8 years and 24.7±3.4 kg/m2, respectively. Mean AHI and RDI were 16.5±15.3/hour and 20.8±14.3/hour, respectively. The mean snoring intensity in the no, mild, moderate, and severe OSA groups was 44.0±2.7, 45.4±6.0, 47.7±5.0, and 50.5±5.6 dB, respectively (P<0.001). There was a positive correlation between snoring intensity and pAHI or PAT RDI (pRDI) (r=0.391 and r=0.385, respectively, both P<0.001). There was also a positive correlation between percent sleep time with the snoring intensity greater than 50 dB and pAHI or pRDI (r=0.423 and r=0.411, respectively, both P<0.001).ConclusionThis study revealed that the intensity of snoring increased with the severity of sleep apnea, which suggests that the loudness of snoring might be an indicator of the severity of OSA

Successful Hemostasis with Recombinant Activated Factor VII in a Patient with Massive Hepatic Subcapsular Hematoma

Recombinant activated coagulation factor VII (rFVIIa) is known to be effective in the management of acquired deficiencies of factor VII and platelet function defects. But recently, rFVIIa has been successfully used to treat ongoing bleeding in disseminated intravascular coagulopathy (DIC) condition. The patient reported here was suspected to be suffering from toxic hepatitis on admission. After percutaneous liver biopsy, bleeding occurred and did not stop even after right hepatic artery embolization. The patient developed a severe hemorrhage that resulted in hypovolemic shock, hemoperitoneum, and a massive subcapsular hematoma. The patient then developed DIC due to massive transfusion, as well as acute liver necrosis. The patient was given 400 μg/kg of rFVIIa. Recombinant factor VIIa was administered in an attempt to control the bleeding. This stabilized the hemoglobin levels of the patient. The patient gradually recovered in 4 months. In conclusion, this case suggests that rFVIIa can be successfully used for the hemostasis of uncontrolled bleeding in DIC

Development and external validation of a deep learning algorithm for prognostication of cardiovascular outcomes

Background and Objectives: We aim to explore the additional discriminative accuracy of a deep learning (DL) algorithm using repeated-measures data for identifying people at high risk for cardiovascular disease (CVD), compared to Cox hazard regression. Methods: Two CVD prediction models were developed from National Health Insurance Service-Health Screening Cohort (NHIS-HEALS): A Cox regression model and a DL model. Performance of each model was assessed in the internal and 2 external validation cohorts in Koreans (National Health Insurance Service-National Sample Cohort; NHIS-NSC) and in Europeans (Rotterdam Study). A total of 412,030 adults in the NHIS-HEALS; 178,875 adults in the NHIS-NSC; and the 4,296 adults in Rotterdam Study were included. Results: Mean ages was 52 years (46% women) and there were 25,777 events (6.3%) in NHIS-HEALS during the follow-up. In internal validation, the DL approach demonstrated a C-statistic of 0.896 (95% confidence interval, 0.886-0.907) in men and 0.921 (0.908-0.934) in women and improved reclassification compared with Cox regression (net reclassification index [NRI], 24.8% in men, 29.0% in women). In external validation with NHIS-NSC, DL demonstrated a C-statistic of 0.868 (0.860-0.876) in men and 0.889 (0.876-0.898) in women, and improved reclassification compared with Cox regression (NRI, 24.9% in men, 26.2% in women). In external validation applied to the Rotterdam Study, DL demonstrated a C-statistic of 0.860 (0.824-0.897) in men and 0.867 (0.830-0.903) in women, and improved reclassification compared with Cox regression (NRI, 36.9% in men, 31.8% in women). Conclusions: A DL algorithm exhibited greater discriminative accuracy than Cox model approaches

Estimating the number of severe COVID-19 cases and COVID-19-related deaths averted by a nationwide vaccination campaign in Republic of Korea

Objectives The Korea Disease Control and Prevention Agency promotes vaccination by regularly providing information on its benefits for reducing the severity of coronavirus disease 2019 (COVID-19). This study aimed to analyze the number of averted severe COVID-19 cases and COVID-19-related deaths by age group and quantify the impact of Republic of Korea’s nationwide vaccination campaign. Methods We analyzed an integrated database from the beginning of the vaccination campaign on February 26, 2021 to October 15, 2022. We estimated the cumulative number of severe cases and COVID-19-related deaths over time by comparing observed and estimated cases among unvaccinated and vaccinated groups using statistical modeling. We compared daily age-adjusted rates of severe cases and deaths in the unvaccinated group to those in the vaccinated group and calculated the susceptible population and proportion of vaccinated people by age. Results There were 23,793 severe cases and 25,441 deaths related to COVID-19. We estimated that 119,579 (95% confidence interval [CI], 118,901–120,257) severe COVID-19 cases and 137,636 (95% CI, 136,909–138,363) COVID-19-related deaths would have occurred if vaccination had not been performed. Therefore, 95,786 (95% CI, 94,659–96,913) severe cases and 112,195 (95% CI, 110,870–113,520) deaths were prevented as a result of the vaccination campaign. Conclusion We found that, if the nationwide COVID-19 vaccination campaign had not been implemented, the number of severe cases and deaths would have been at least 4 times higher. These findings suggest that Republic of Korea’s nationwide vaccination campaign reduced the number of severe cases and COVID-19 deaths

Early Compliance and Efficacy of Sublingual Immunotherapy in Patients with Allergic Rhinitis for House Dust Mites

Objectives. Sublingual immunotherapy (SLIT) has recently received much attention around the world as a treatment for allergic rhinitis. This study aimed to investigate the efficacy and adverse effects of SLIT in Korean patients with allergic rhinitis caused by house dust mites. The treatment compliance and the patient satisfaction with SLIT were also assessed. Methods. The patients who were sensitized to Dermatophagoides pteronyssinus and Dermatophagoides farinae and who started SLIT between November 2007 and July 2008 were included in this study. The symptom questionnaires, which included items on rhinorrhea, sneezing, nasal obstruction, itchy nose, olfactory disturbance, eye discomfort and sleep disturbance, were obtained before and 6 months after SLIT. The patient satisfaction and the adverse effects were also investigated. Results. One hundred forty-two patients started SLIT and 98 of them continued SLIT for 6 months or more. Ninety-two of the 98 patients completed the questionnaires. The duration of receiving SLIT was 9.8 months on average (range, 6 to 13 months). All the symptoms of allergic rhinitis were improved with SLIT. Forty-five percent of the patients were satisfied for SLIT, while 12% were unsatisfied. The incidence of adverse effects was 12% during maintenance therapy, although it was 48% during the up-dosing phase. The drop-out rate of SLIT was 31.0%. Conclusion. The subjective symptoms were improved with SLIT in Korean patients with allergic rhinitis for house dust mites. Yet the drop out rate was high despite of the symptomatic improvement.Roder E, 2008, CLIN EXP ALLERGY, V38, P1659, DOI 10.1111/j.1365-2222.2008.03060.xEsch RE, 2008, CURR OPIN OTOLARYNGO, V16, P260Frew AJ, 2008, NEW ENGL J MED, V358, P2259BOUSQUET J, 2008, ALLERGY S, V86, P8Eifan AO, 2007, ALLERGY, V62, P567, DOI 10.1111/j.1398-9995.2006.01301.xDunsky EH, 2006, ALLERGY, V61, P1235, DOI 10.1111/j.1398-9995.2006.01137.xAntico A, 2006, ALLERGY, V61, P1236, DOI 10.1111/j.1398-9995.2006.01155.xDahl R, 2006, J ALLERGY CLIN IMMUN, V118, P434, DOI 10.1016/j.jaci.2006.05.003Durham SR, 2006, J ALLERGY CLIN IMMUN, V117, P802, DOI 10.1016/j.jaci.2005.12.1358Passlacqua G, 2006, J ALLERGY CLIN IMMUN, V117, P946, DOI 10.1016/j.jaci.2005.12.1312Canonica GW, 2006, ALLERGY, V61, P20PASSALACQUA G, 2006, INFLAMM ALLERGY DRUG, V5, P43RIENZO VD, 2005, CLIN EXP ALLERGY, V35, P560KIM DY, 2004, KOREAN J OTOLARYNGOL, V47, P132WILSON DR, 2003, COCHRANE DB SYST REV, P2893NUHOGLU Y, 2003, J INVESTIG ALLERGOL, V17, P375Lombardi C, 2001, ALLERGY, V56, P989Guez S, 2000, ALLERGY, V55, P369, DOI 10.1034/j.1398-9995.2000.00413.xPurello-D`Ambrosio F, 1999, ALLERGY, V54, P968Pradalier A, 1999, ALLERGY, V54, P819Durham SR, 1996, J ALLERGY CLIN IMMUN, V97, P1356CASANOVAS M, 1994, J INVEST ALLERG CLIN, V4, P305

Highly malignant soft tissue sarcoma of the extremity with a delayed diagnosis

<p>Abstract</p> <p>Purpose</p> <p>To evaluate the characteristics of highly malignant soft tissue sarcoma of the extremity with a delayed diagnosis.</p> <p>Materials and methods</p> <p>The clinical and radiological characteristics of 18 cases of highly malignant soft tissue sarcomas of the extremity with a delayed diagnosis were determined.</p> <p>Results</p> <p>Ten men and eight women of mean age 44.8 years (range, 15-79 years) were included in this study. Seven cases of synovial sarcoma, three cases each of alveolar soft part sarcoma and malignant fibrous histiocytoma, two cases each of highly malignant leiomyosarcoma and myxofibrosarcoma, and one case of clear cell sarcoma were enrolled. Times from tumor detection to diagnosis ranged from 1 to 3 years in most cases; three of the seven synovial sarcoma cases took more than 10 years to diagnose. Of the seven cases of synovial sarcoma, five cases of small, superficial located masses were simply excised without a pre-surgical biopsy. Three cases of alveolar soft part sarcoma showed characteristic T1- and T2-weighted high signal intensities with signal voids in MR images. In addition, one synovial sarcoma patient and one alveolar soft part sarcoma patient showed evidence of calcification on plain radiographs. However, no general characteristic clinical findings were found to be common to the 18 cases.</p> <p>Conclusions</p> <p>Contrary to general expectations, some soft tissue tumors that grow slowly are painless, and those that occur in superficial limbs may be highly malignant. Thus, even when a slow growing, painless superficial mass is encountered in a limb, physicians should keep the possibility of highly malignant soft tissue sarcoma in mind.</p

Development and verification of prediction models for preventing cardiovascular diseases

Objectives Cardiovascular disease (CVD) is one of the major causes of death worldwide. For improved accuracy of CVD prediction, risk classification was performed using national time-series health examination data. The data offers an opportunity to access deep learning (RNN-LSTM), which is widely known as an outstanding algorithm for analyzing time-series datasets. The objective of this study was to show the improved accuracy of deep learning by comparing the performance of a Cox hazard regression and RNN-LSTM based on survival analysis. Methods and findings We selected 361,239 subjects (age 40 to 79 years) with more than two health examination records from 2002–2006 using the National Health Insurance System-National Health Screening Cohort (NHIS-HEALS). The average number of health screenings (from 2002–2013) used in the analysis was 2.9 ± 1.0. Two CVD prediction models were developed from the NHIS-HEALS data: a Cox hazard regression model and a deep learning model. In an internal validation of the NHIS-HEALS dataset, the Cox regression model showed a highest time-dependent area under the curve (AUC) of 0.79 (95% CI 0.70 to 0.87) for in females and 0.75 (95% CI 0.70 to 0.80) in males at 2 years. The deep learning model showed a highest time-dependent AUC of 0.94 (95% CI 0.91 to 0.97) for in females and 0.96 (95% CI 0.95 to 0.97) in males at 2 years. Layer-wise Relevance Propagation (LRP) revealed that age was the variable that had the greatest effect on CVD, followed by systolic blood pressure (SBP) and diastolic blood pressure (DBP), in that order. Conclusion The performance of the deep learning model for predicting CVD occurrences was better than that of the Cox regression model. In addition, it was confirmed that the known risk factors shown to be important by previous clinical studies were extracted from the study results using LRP

Exendin-4 Improves Steatohepatitis by Increasing Sirt1 Expression in High-Fat Diet-Induced Obese C57BL/6J Mice

The effects of exendin-4 on Sirt1 expression as a mechanism of reducing fatty liver have not been previously reported. Therefore, we investigated whether the beneficial effects of exendin-4 treatment on fatty liver are mediated via Sirt1 in high-fat (HF) diet-induced obese C57BL/6J mice and related cell culture models. Exendin-4 treatment decreased body weight, serum free fatty acid (FA), and triglyceride levels in HF-induced obese C57BL/6J mice. Histological analysis showed that exendin-4 reversed HF-induced hepatic accumulation of lipids and inflammation. Exendin-4 treatment increased mRNA and protein expression of Sirt1 and its downstream factor, AMPK, in vivo and also induced genes associated with FA oxidation and glucose metabolism. In addition, a significant increase in the hepatic expression of Lkb1 and Nampt mRNA was observed in exendin-4-treated groups. We also observed increased expression of phospho-Foxo1 and GLUT2, which are involved in hepatic glucose metabolism. In HepG2 and Huh7 cells, mRNA and protein expressions of GLP-1R were increased by exendin-4 treatment in a dose-dependent manner. Exendin-4 enhanced protein expression of Sirt1 and phospho-AMPKα in HepG2 cells treated with 0.4 mM palmitic acid. We also found that Sirt1 was an upstream regulator of AMPK in hepatocytes. A novel finding of this study was the observation that expression of GLP-1R is proportional to exendin-4 concentration and exendin-4 could attenuate fatty liver through activation of Sirt1