The Longitudinal Association between Multiple Frailty Criteria and Depressive Symptomatology Five Years Later in Older Adults: A Decision Tree Modelling Approach.

: To examine the longitudinal association between frailty criteria and depression (DEP) in a large sample of older Europeans using decision tree models, and to examine complex relationships between frailty criteria and DEP symptomatology. : Data come from waves six and eight of the Population Survey of Health, Ageing and Retirement in Europe. DEP was assessed using the EURO-D scale (wave 8) and frailty (wave 6).

Effects of a music-based intervention on psychophysiological outcomes of patients undergoing medical imaging procedures: A systematic review and meta-analysis.

Introduction: Musical intervention (MI) is a valuable strategy for addressing the psychological and emotional challenges faced by patients undergoing imaging procedures. This study explores MI's impact on psychophysiological outcomes during imaging procedures, detailing the sound repertoire and technical characteristics employed in MI.

Methods: A systematic review (SR) and meta-analysis (MA) were conducted.

An Approach to Binary Classification of Alzheimer's Disease Using LSTM.

In this study, we use LSTM (Long-Short-Term-Memory) networks to evaluate Magnetic Resonance Imaging (MRI) data to overcome the shortcomings of conventional Alzheimer's disease (AD) detection techniques. Our method offers greater reliability and accuracy in predicting the possibility of AD, in contrast to cognitive testing and brain structure analyses. We used an MRI dataset that we downloaded from the Kaggle source to train our LSTM network.

Unveiling the Potential Distribution of the Highly Threatened Madeira Pipistrelle (): Do Different Evolutionary Significant Units Exist?

The isolation of islands has played a significant role in shaping the unique evolutionary histories of many species of flora and fauna, including bats. One notable example is the Madeira pipistrelle (), which inhabits the Macaronesian archipelagos of the Azores, Madeira, and the Canary Islands. Despite the high biogeographic and conservation importance of this species, there is limited information on its ecology and evolutionary history across different archipelagos.

Non-Destructive Banana Ripeness Detection Using Shallow and Deep Learning: A Systematic Review.

The ripeness of bananas is the most significant factor affecting nutrient composition and demand. Conventionally, cutting and ripeness analysis requires expert knowledge and substantial human intervention, and different studies have been conducted to automate and substantially reduce human effort. Using the Preferred Reporting Items for the Systematic Reviews approach, 1548 studies were extracted from journals and conferences, using different research databases, and 35 were included in the final review for key parameters.

Novel Comparative Study for the Detection of COVID-19 Using CT Scan and Chest X-ray Images.

The number of coronavirus disease (COVID-19) cases is constantly rising as the pandemic continues, with new variants constantly emerging. Therefore, to prevent the virus from spreading, coronavirus cases must be diagnosed as soon as possible. The COVID-19 pandemic has had a devastating impact on people's health and the economy worldwide.

Association between the Duration of the Active Commuting to and from School, and Cognitive Performance in Urban Portuguese Adolescents.

This study aimed to analyze the differences between active commuting to school (ACS) and non-ACS in cognitive performance (CP), and the association of ACS duration with CP. This cross-sectional study included 370 adolescents (males = 170), with a mean age of 15.28 ± 2.

Multiple Time Series Fusion Based on LSTM: An Application to CAP A Phase Classification Using EEG.

The Cyclic Alternating Pattern (CAP) is a periodic activity detected in the electroencephalogram (EEG) signals. This pattern was identified as a marker of unstable sleep with several possible clinical applications; however, there is a need to develop automatic methodologies to facilitate real-world applications based on CAP assessment. Therefore, a deep learning-based EEG channels' feature level fusion was proposed in this work and employed for the CAP A phase classification.

Heuristic Optimization of Deep and Shallow Classifiers: An Application for Electroencephalogram Cyclic Alternating Pattern Detection.

Methodologies for automatic non-rapid eye movement and cyclic alternating pattern analysis were proposed to examine the signal from one electroencephalogram monopolar derivation for the A phase, cyclic alternating pattern cycles, and cyclic alternating pattern rate assessments. A population composed of subjects free of neurological disorders and subjects diagnosed with sleep-disordered breathing was studied. Parallel classifications were performed for non-rapid eye movement and A phase estimations, examining a one-dimension convolutional neural network (fed with the electroencephalogram signal), a long short-term memory (fed with the electroencephalogram signal or with proposed features), and a feed-forward neural network (fed with proposed features), along with a finite state machine for the cyclic alternating pattern cycle scoring.

On the use of patterns obtained from LSTM and feature-based methods for time series analysis: application in automatic classification of the CAP A phase subtypes.

. The cyclic alternating pattern is a marker of sleep instability identified in the electroencephalogram signals whose sequence of transient variations compose the A phases. These phases are divided into three subtypes (A1, A2, and A3) according to the presented patterns.

Machine Learning for Brain Stroke: A Review.

Machine Learning (ML) delivers an accurate and quick prediction outcome and it has become a powerful tool in health settings, offering personalized clinical care for stroke patients. An application of ML and Deep Learning in health care is growing however, some research areas do not catch enough attention for scientific investigation though there is real need of research. Therefore, the aim of this work is to classify state-of-arts on ML techniques for brain stroke into 4 categories based on their functionalities or similarity, and then review studies of each category systematically.

An Oximetry Based Wireless Device for Sleep Apnea Detection.

Sleep related disorders can severely disturb the quality of sleep. Among these disorders, obstructive sleep apnea (OSA) is highly prevalent and commonly undiagnosed. Polysomnography is considered to be the gold standard exam for OSA diagnosis.

Matrix of Lags: A tool for analysis of multiple dependent time series applied for CAP scoring.

Background: Multiple methods have been developed to assess what happens between and within time series. In a particular type of these series, the previous values of the currently observed series are contingent on the lagged values of another series. These cases can commonly be addressed by regression.

Development of Physical Performance Tasks during Rapid Growth in Brazilian Children: The Cariri Healthy Growth Study.

Growth and physical performance scores were studied around three years of attainment of peak height velocity (PHV). We aimed to estimate the age at peak velocity, or at peak rate, in physical performance tasks, and sex-differences when aligned by biological age. A total of 131 boys and 123 girls, 8 to 14 years of age were recruited from the Cariri region of Brazil.

A Systematic Review of Detecting Sleep Apnea Using Deep Learning.

Sleep apnea is a sleep related disorder that significantly affects the population. Polysomnography, the gold standard, is expensive, inaccessible, uncomfortable and an expert technician is needed to score. Numerous researchers have proposed and implemented automatic scoring processes to address these issues, based on fewer sensors and automatic classification algorithms.

Healthy Lifestyle in Children and Adolescents and Its Association with Subjective Health Complaints: Findings from 37 Countries and Regions from the HBSC Study.

Background: It is important to clearly understand the factors associated with subjective health complaints. The study aimed to investigate the relationship between subjective health complaints, several health behaviors, and a composite measure of healthy lifestyle.

Methods: Data were from the Health Behaviour in School-aged Children (HBSC) 2014 international database.

Developmental and physical-fitness associations with gross motor coordination problems in Peruvian children.

The aims of this cross-sectional study were to examine the developmental characteristics (biological maturation and body size) associated with gross motor coordination problems in 5193 Peruvian children (2787 girls) aged 6-14 years from different geographical locations, and to investigate how the probability that children suffer with gross motor coordination problems varies with physical fitness. Children with gross motor coordination problems were more likely to have lower flexibility and explosive strength levels, having adjusted for age, sex, maturation and study site. Older children were more likely to suffer from gross motor coordination problems, as were those with greater body mass index.

Experimental and numerical characterization of a hybrid Fabry-Pérot cavity for temperature sensing.

A hybrid Fabry-Pérot cavity sensing head based on a four-bridge microstructured fiber is characterized for temperature sensing. The characterization of this cavity is performed numerically and experimentally in the L-band. The sensing head output signal presents a linear variation with temperature changes, showing a sensitivity of 12.

Centile curves and reference values for height, body mass, body mass index and waist circumference of Peruvian children and adolescents.

This study aimed to provide height, body mass, BMI and waist circumference (WC) growth centile charts for school-children, aged 4-17 years, from central Peru, and to compare Peruvian data with North-American and Argentinean references. The sample consisted of 8753 children and adolescents (4130 boys and 4623 girls) aged 4 to 17 years, from four Peruvian cities: Barranco, La Merced, San Ramón and Junín. Height, body mass and WC were measured according to standardized techniques.