Long-term musical training induces white matter plasticity in emotion and language networks.

Numerous studies have reported that long-term musical training can affect brain functionality and induce structural alterations in the brain. Singing is a form of vocal musical expression with an unparalleled capacity for communicating emotion; however, there has been relatively little research on neuroplasticity at the network level in vocalists (i.e.

PADAr: physician-oriented artificial intelligence-facilitating diagnosis aid for retinal diseases.

Retinopathy screening via digital imaging is promising for early detection and timely treatment, and tracking retinopathic abnormality over time can help to reveal the risk of disease progression. We developed an innovative physician-oriented artificial intelligence-facilitating diagnosis aid system for retinal diseases for screening multiple retinopathies and monitoring the regions of potential abnormality over time. Our dataset contains 4908 fundus images from 304 eyes with image-level annotations, including diabetic retinopathy, age-related macular degeneration, cellophane maculopathy, pathological myopia, and healthy control (HC).

Fuzzy logic-based mobile computing system for hand rehabilitation after neurological injury.

Background: Effective neurological rehabilitation requires long term assessment and treatment. The rapid progress of virtual reality-based assistive technologies and tele-rehabilitation has increased the potential for self-rehabilitation of various neurological injuries under clinical supervision.

Objective: The objective of this study was to develop a fuzzy inference mechanism for a smart mobile computing system designed to support in-home rehabilitation of patients with neurological injury in the hand by providing an objective means of self-assessment.

Continued use of an interactive computer game-based visual perception learning system in children with developmental delay.

This study developed an interactive computer game-based visual perception learning system for special education children with developmental delay. To investigate whether perceived interactivity affects continued use of the system, this study developed a theoretical model of the process in which learners decide whether to continue using an interactive computer game-based visual perception learning system. The technology acceptance model, which considers perceived ease of use, perceived usefulness, and perceived playfulness, was extended by integrating perceived interaction (i.

Effects of B Value on Quantification of Rapid Diffusion Kurtosis Imaging in Normal and Acute Ischemic Brain Tissues.

Purpose: Diffusion kurtosis imaging (DKI) has been widely used to characterize brain tissue alterations. Diffusion-weighting factor or b value plays an important role in the measurement of rapid DKI and may have influential effects on them. The purpose of this study was to investigate the effects of b value on rapid DKI indices in normal and acute ischemic brain tissues.

Epidemiology of cancer in end-stage renal disease dialysis patients: a national cohort study in Taiwan.

The incidence and mortality of site-specific cancers in patients with end-stage renal disease (ESRD) on maintenance dialysis have been rarely studied for Asian populations. We tapped Taiwan`s National Health Insurance Research Database to identify and recruit patients starting maintenance dialysis between 1999 and 2004. They were followed from initiation of dialysis until death, discontinuation of dialysis, or the end of 2008.

Death Does Matter--Cancer Risk in Patients With End-Stage Renal Disease: A Nationwide Population-Based Study With Competing Risk Analyses.

Patients with end-stage renal disease (ESRD) have a high mortality rate. We hypothesized that not accounting for death as a competing risk overestimates the event rate caused by ESRD. Thus, we examined the cancer risk for patients with ESRD (ESRD) after death as a competing risk event had been adjusted for.

Exploration of the importance of geriatric frailty on health-related quality of life.

Aim: The ageing of the population is a demographic trend globally. Promoting the health of elderly persons has become a crucial priority. However, knowledge about the relationship between frailty and quality of life (QoL) remains limited.

Comparisons of Reproducibility and Mean Values of Diffusion Tensor Imaging-Derived Indices between Unipolar and Bipolar Diffusion Pulse Sequences.

Eddy current distortion is an important issue that may influence the quantitative measurements of diffusion tensor imaging (DTI). The corrections of eddy current artifacts could be performed using bipolar diffusion gradients or unipolar gradients with affine registration. Whether the diffusion pulse sequence affects the quantification of DTI indices and the technique that produces more reliable DTI indices in terms of reproducibility both remain unclear.

Volume-outcome associations after major hepatectomy for hepatocellular carcinoma: a nationwide Taiwan study.

Objective: The objective of this study was to explore volume-outcome associations after major hepatectomy for hepatocellular carcinoma (HCC).

Methods: This population-based cohort study retrospectively analyzed 23,107 major hepatectomies for HCC patients from 1998 to 2009. Relationships between hospital/surgeon volume and patient outcome were analyzed by propensity score matching (PSM).

Leuconostoc mesenteroides growth in food products: prediction and sensitivity analysis by adaptive-network-based fuzzy inference systems.

Background: An adaptive-network-based fuzzy inference system (ANFIS) was compared with an artificial neural network (ANN) in terms of accuracy in predicting the combined effects of temperature (10.5 to 24.5°C), pH level (5.

Using Akaike information criterion and minimum mean square error mode in compensating for ultrasonographic errors for estimation of fetal weight by new operators.

Objectives: The accuracy of ultrasound (US) measurements is operator dependent. In order to decrease the operator-dependent errors in estimated fetal weight (EFW), a model selection analysis was undertaken to select significant compensation weighting factors on ultrasonographic parameters to support artificial neural network (ANN), and thus to enhance the accuracy of fetal weight estimation.

Materials And Methods: In total, 2127 singletons were examined by prenatal US within 3 days before delivery for ANN development, and another 100 cases were selected from new operators for evaluation.

Comparison of classification algorithms with wrapper-based feature selection for predicting osteoporosis outcome based on genetic factors in a taiwanese women population.

An essential task in a genomic analysis of a human disease is limiting the number of strongly associated genes when studying susceptibility to the disease. The goal of this study was to compare computational tools with and without feature selection for predicting osteoporosis outcome in Taiwanese women based on genetic factors such as single nucleotide polymorphisms (SNPs). To elucidate relationships between osteoporosis and SNPs in this population, three classification algorithms were applied: multilayer feedforward neural network (MFNN), naive Bayes, and logistic regression.

Efficient fetal size classification combined with artificial neural network for estimation of fetal weight.

Objectives: A novel analysis was undertaken to select a significant ultrasonographic parameter (USP) for classifying fetuses to support artificial neural network (ANN), and thus to enhance the accuracy of fetal weight estimation.

Methods: In total, 2127 singletons were examined by prenatal ultrasound within 3 days before delivery. First, correlation analysis was used to determine a significant USP for fetal grouping.

A hospital registration system using syndromes' descriptions analysis and information retrieval technology.

Correct registration in the hospital can avoid wasting medical resources and shorten the time of diagnoses. The purpose of this research is to build a hospital registration system to help patients register in the hospital. This system can assist patients, who are not familiar with medical topics, to determine which department they should register by the spontaneous descriptions.

A two-stage approach to positioning and identification of tracheal intubation using LED-based lightwand and acoustic models.

This paper proposes a two-stage approach to positioning and identifying tracheal intubations by computer-assisted diagnosis system. First, an innovated LED-based lightwand is developed for positioning the opening of the trachea and inserting the endotracheal tube rapidly. The proposed LED-based lightwand instrument significantly reduces the effects of temperature reaction without changing transillumination through the tissue.

Computer-aided auscultation learning system for nursing technique instruction.

Pulmonary auscultation is a physical assessment skill learned by nursing students for examining the respiratory system. Generally, a sound simulator equipped mannequin is used to group teach auscultation techniques via classroom demonstration. However, nursing students cannot readily duplicate this learning environment for self-study.

Joint optimization of word alignment and epenthesis generation for Chinese to Taiwanese sign synthesis.

This work proposes a novel approach to translate Chinese to Taiwanese sign language and to synthesize sign videos. An aligned bilingual corpus of Chinese and Taiwanese Sign Language (TSL) with linguistic and signing information is also presented for sign language translation. A two-pass alignment in syntax level and phrase level is developed to obtain the optimal alignment between Chinese sentences and Taiwanese sign sequences.

Text generation from Taiwanese Sign Language using a PST-based language model for augmentative communication.

This paper proposes a novel approach to the generation of Chinese sentences from ill-formed Taiwanese Sign Language (TSL) for people with hearing impairments. First, a sign icon-based virtual keyboard is constructed to provide a visualized interface to retrieve sign icons from a sign database. A proposed language model (LM), based on a predictive sentence template (PST) tree, integrates a statistical variable n-gram LM and linguistic constraints to deal with the translation problem from ill-formed sign sequences to grammatical written sentences.

Error-tolerant sign retrieval using visual features and maximum a posteriori estimation.

This paper proposes an efficient error-tolerant approach to retrieving sign words from a Taiwanese Sign Language (TSL) database. This database is tagged with visual gesture features and organized as a multilist code tree. These features are defined in terms of the visual characteristics of sign gestures by which they are indexed for sign retrieval and displayed using an anthropomorphic interface.