Multi-objective Non-intrusive Hearing-aid Speech Assessment Model

Without the need for a clean reference, non-intrusive speech assessment methods have caught great attention for objective evaluations. While deep learning models have been used to develop non-intrusive speech assessment methods with promising results, there is limited research on hearing-impaired subjects. This study proposes a multi-objective non-intrusive hearing-aid speech assessment model, called HASA-Net Large, which predicts speech quality and intelligibility scores based on input speech signals and specified hearing-loss patterns. Our experiments showed the utilization of pre-trained SSL models leads to a significant boost in speech quality and intelligibility predictions compared to using spectrograms as input. Additionally, we examined three distinct fine-tuning approaches that resulted in further performance improvements. Furthermore, we demonstrated that incorporating SSL models resulted in greater transferability to OOD dataset. Finally, this study introduces HASA-Net Large, which is a non-invasive approach for evaluating speech quality and intelligibility. HASA-Net Large utilizes raw waveforms and hearing-loss patterns to accurately predict speech quality and intelligibility levels for individuals with normal and impaired hearing and demonstrates superior prediction performance and transferability

Study on the Correlation between Objective Evaluations and Subjective Speech Quality and Intelligibility

Subjective tests are the gold standard for evaluating speech quality and intelligibility, but they are time-consuming and expensive. Thus, objective measures that align with human perceptions are crucial. This study evaluates the correlation between commonly used objective measures and subjective speech quality and intelligibility using a Chinese speech dataset. Moreover, new objective measures are proposed combining current objective measures using deep learning techniques to predict subjective quality and intelligibility. The proposed deep learning model reduces the amount of training data without significantly impacting prediction performance. We interpret the deep learning model to understand how objective measures reflect subjective quality and intelligibility. We also explore the impact of including subjective speech quality ratings on speech intelligibility prediction. Our findings offer valuable insights into the relationship between objective measures and human perceptions

Prognostic factors associated with the survival of oral and pharyngeal carcinoma in Taiwan

<p>Abstract</p> <p>Background</p> <p>In Taiwan, a distinct ethnic group variation in incidence and mortality rates has been suggested for most carcinomas. Our aim is to identify the role of prognostic factors associated with the survival of oral and pharyngeal carcinoma in Taiwan.</p> <p>Methods</p> <p>Taiwan Cancer Registry records of 9039 subjects diagnosed with oral and pharyngeal carcinoma were analyzed. The population was divided into three ethnic groups by residence, which were Taiwanese aborigines, Hakka and Hokkien communities. Five-year survival rates were estimated by Kaplan-Meier methods. Ethnic curves differed significantly by log-rank test; therefore separate models for Taiwanese aborigines, Hakka and Hokkien were carried out. The Cox multivariate proportional hazards model was used to examine the role of prognostic factors on ethnic survival.</p> <p>Results</p> <p>The five-year survival rates of oral and pharyngeal carcinoma were significantly poorer for Hokkien community (53.9%) and Taiwanese aborigines community (58.1%) compared with Hakka community (60.5%). The adjusted hazard ratio of Taiwanese aborigines versus Hakka was 1.07 (95%CI, 0.86–1.33) for oral and pharyngeal carcinoma mortality, and 1.16 (95%CI, 1.01–1.33) for Hokkien versus Hakka. Males had significantly poor prognosis than females. Subjects with tongue and/or mouth carcinoma presented the worst prognosis, whereas lip carcinoma had the best prognosis. Subjects with verrucous carcinoma had better survival than squamous cell carcinoma. Prognosis was the worst in elderly subjects, and subjects who underwent surgery had the highest survival rate.</p> <p>Conclusion</p> <p>Our study presented that predictive variables in oral and pharyngeal carcinoma survival have been: ethnic groups, period of diagnosis, gender, diagnostic age, anatomic site, morphologic type, and therapy.</p

Effects of Transapical Transcatheter Mitral Valve Implantation

Purpose: In this study, transapical transcatheter mitral valve-in-valve implantation (TAMVI) was compared with surgical redo mitral valve replacement (SRMVR) in terms of clinical outcomes.Methods: We retrospectively identified patients with degenerated mitral bioprosthesis or failed annuloplasty rings who underwent redo SRMVR or TAMVI at our medical center. Clinical outcomes were based on echocardiography results.Results: We retrospectively identified patients with symptomatic mitral bioprosthetic valve dysfunction (n = 58) and failed annuloplasty rings (n = 14) who underwent redo SRMVR (n = 36) or TAMVI (n = 36). The Society of Thoracic Surgeons Predicted Risk of Mortality scores were higher in the TAMVI group (median: 9.52) than in the SRMVR group (median: 5.59) (p-value = 0.02). TAMVI patients were more severe in New York Heart Association (p-value = 0.04). The total procedure time (skin to skin) and length of stay after procedures were significantly shorter in the TAMVI group, and no significant difference in mortality was noted after adjustment for confounding factors (p-value = 0.11). The overall mean mitral valve pressure gradient was lower in the TAMVI group than in the SRMVR group at 24 months (p &lt; 0.01). Both groups presented a decrease in the severity of mitral and tricuspid regurgitation at 3–24 months.Conclusions: In conclusion, the statistical analysis is still not robust enough to make a claim that TAMVI is an appropriate alternative. The outcome of the patient appears only to be related to the patient's pre-operative STS score. Additional multi-center, longitudinal studies are warranted to adequately assess the effect of TAMVI

Women with endometriosis have higher comorbidities: Analysis of domestic data in Taiwan

AbstractEndometriosis, defined by the presence of viable extrauterine endometrial glands and stroma, can grow or bleed cyclically, and possesses characteristics including a destructive, invasive, and metastatic nature. Since endometriosis may result in pelvic inflammation, adhesion, chronic pain, and infertility, and can progress to biologically malignant tumors, it is a long-term major health issue in women of reproductive age. In this review, we analyze the Taiwan domestic research addressing associations between endometriosis and other diseases. Concerning malignant tumors, we identified four studies on the links between endometriosis and ovarian cancer, one on breast cancer, two on endometrial cancer, one on colorectal cancer, and one on other malignancies, as well as one on associations between endometriosis and irritable bowel syndrome, one on links with migraine headache, three on links with pelvic inflammatory diseases, four on links with infertility, four on links with obesity, four on links with chronic liver disease, four on links with rheumatoid arthritis, four on links with chronic renal disease, five on links with diabetes mellitus, and five on links with cardiovascular diseases (hypertension, hyperlipidemia, etc.). The data available to date support that women with endometriosis might be at risk of some chronic illnesses and certain malignancies, although we consider the evidence for some comorbidities to be of low quality, for example, the association between colon cancer and adenomyosis/endometriosis. We still believe that the risk of comorbidity might be higher in women with endometriosis than that we supposed before. More research is needed to determine whether women with endometriosis are really at risk of these comorbidities

Composite Wavelet Filters for Enhanced Automated Target Recognition

Automated Target Recognition (ATR) systems aim to automate target detection, recognition, and tracking. The current project applies a JPL ATR system to low-resolution sonar and camera videos taken from unmanned vehicles. These sonar images are inherently noisy and difficult to interpret, and pictures taken underwater are unreliable due to murkiness and inconsistent lighting. The ATR system breaks target recognition into three stages: 1) Videos of both sonar and camera footage are broken into frames and preprocessed to enhance images and detect Regions of Interest (ROIs). 2) Features are extracted from these ROIs in preparation for classification. 3) ROIs are classified as true or false positives using a standard Neural Network based on the extracted features. Several preprocessing, feature extraction, and training methods are tested and discussed in this paper

Effectiveness of Multidisciplinary Care for Chronic Kidney Disease: A Systematic Review.

BackgroundChronic kidney disease (CKD) is a common chronic disease. As this disease is extremely complex, multidisciplinary care (MDC) is needed to provide complete and continuous care.AimA systematic literature review was performed to examine the constituents of MDC, the content of MDC interventions, and the health outcomes in CKD patients receiving MDC.MethodsSearches of five Chinese and English databases for studies of CKD patients who had received MDC from 2007 to 2019 revealed 11 studies, which comprised 16,066 CKD patients. The Physiotherapy Evidence Database scale (Physiotherapy Evidence Database, 2017) was used to appraise study quality for randomized controlled trials, and the Joanna Briggs Institute Critical Appraisal tools (Joanna Briggs Institute, 2017) were for cohort studies.ResultsThe MDC teams that provided comprehensive medical care for these patients included nephrologists, nurses, surgeons, general practitioners, pharmacists, psychotherapists, social workers, nutritionists, and other specialists. The literature review revealed that MDC for CKD slows the decline in estimated glomerular filtration rate and decreases patient mortality, the risk of renal replacement therapy, the need for emergent dialysis, and annual medical costs. Analyses of biochemical markers in the CKD patients showed that MDC improves control of serum levels of calcium and phosphate, improves control of parathyroid hormone, and reduces proteinuria and fasting blood glucose values. However, further studies are needed to determine the effects of MDC on all-cause mortality, blood pressure control, hospitalization rate, hospitalization for cardiovascular or infection events, medications use, and other biochemical markers in CKD patients.Linking evidence to actionCross-disciplinary collaboration of healthcare professionals is needed to ensure that patients undergo regular follow-up and periodic assessment of clinical status, in addition to ensuring that relevant resources and assistance are provided in a timely manner. A follow-up period of at least 2&nbsp;years is also needed to ensure sufficient time to observe MDC results

Synergistic Effects of Weighted Genetic Risk Scores and Resistin and sST2 Levels on the Prognostication of Long-Term Outcomes in Patients with Coronary Artery Disease

Resistin and soluble suppression of tumorigenicity 2 (sST2) are useful predictors in patients with coronary artery disease (CAD). Their serum levels are significantly attributed to variations in RETN and IL1RL1 loci. We investigated candidate variants in the RETN locus for resistin levels and those in the IL1RL1 locus for sST2 levels and evaluated the prognostication of these two biomarkers and the corresponding variants for long-term outcomes in the patients with CAD. We included 4652, 557, and 512 Chinese participants from the Taiwan Biobank (TWB), cardiovascular health examination (CH), and CAD cohorts, respectively. Candidate variants in RETN and IL1RL1 were investigated using whole-genome sequence (WGS) and genome-wide association study (GWAS) data in the TWB cohort. The weighted genetic risk scores (WGRS) of RETN and IL1RL1 with resistin and sST2 levels were calculated. Kaplan&ndash;Meier curves were used to analyze the prognostication of resistin and sST2 levels, WGRS of RETN and IL1RL1, and their combinations. Three RETN variants (rs3219175, rs370006313, and rs3745368) and two IL1RL1 variants (rs10183388 and rs4142132) were independently associated with resistin and sST2 levels as per the WGS and GWAS data in the TWB cohort and were further validated in the CH and CAD cohorts. In combination, these variants explained 53.7% and 28.0% of the variation in resistin and sST2 levels, respectively. In the CAD cohort, higher resistin and sST2 levels predicted higher rates of all-cause mortality and major adverse cardiac events (MACEs) during long-term follow-up, but WGRS of RETN and IL1RL1 variants had no impact on these outcomes. A synergistic effect of certain combinations of biomarkers with RETN and IL1RL1 variants was found on the prognostication of long-term outcomes: Patients with high resistin levels/low RETN WGRS and those with high sST2 levels/low IL1RL1 WGRS had significantly higher all-cause mortality and MACEs rates, and those with both these combinations had the poorest outcomes. Both higher resistin and sST2 levels, but not RETN and IL1RL1 variants, predict poor long-term outcomes in patients with CAD. Furthermore, combining resistin and sST2 levels with the WGRS of RETN and IL1RL1 genotyping exerts a synergistic effect on the prognostication of CAD outcomes. Future studies including a large sample size of participants with different ethnic populations are needed to verify this finding