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View article: An exploratory study on predicting depressive symptoms in autistic individuals using wearable devices and machine learning
An exploratory study on predicting depressive symptoms in autistic individuals using wearable devices and machine learning Open
Digital phenotypes derived from wearable devices may facilitate the detection of depressive symptoms in autistic adults, offering potential benefits for clinical assessments and emotion self-care.
View article: Simplifying Knee OA Prognosis: A Deep Learning Approach Using Radiographs and Minimal Clinical Inputs
Simplifying Knee OA Prognosis: A Deep Learning Approach Using Radiographs and Minimal Clinical Inputs Open
Objectives: To predict the progression of knee osteoarthritis (OA), a deep convolutional neural network model was developed and applied to basic images and clinical data. Design: A vision transformer-based model was trained using 5565 knee…
View article: Improved UNet-Based Detection of 3D Cotton Cup Indentations and Analysis of Automatic Cutting Accuracy
Improved UNet-Based Detection of 3D Cotton Cup Indentations and Analysis of Automatic Cutting Accuracy Open
With the advancement of intelligent technology and the rise in labor costs, manual identification and cutting of 3D cotton cup indentations can no longer meet modern demands. The increasing variety and shape of 3D cotton cups due to person…
View article: Effects of Heat Adaptation Behaviors on Resting Heart Rate Response to Summer Temperatures in Older Adults: Wearable Device Panel Study
Effects of Heat Adaptation Behaviors on Resting Heart Rate Response to Summer Temperatures in Older Adults: Wearable Device Panel Study Open
Background The health impact of summer heat on older adults is a growing public concern, yet the physiological responses, particularly changes in resting heart rate (RHR), and the role of personal heat adaptation behaviors remain underexpl…
View article: Real-time fall detection with ground height awareness using LiDAR and a camera of a mobile device
Real-time fall detection with ground height awareness using LiDAR and a camera of a mobile device Open
View article: A novel missense variant of FBN1 gene in a Sardinian family with Marfan syndrome: a case report
A novel missense variant of FBN1 gene in a Sardinian family with Marfan syndrome: a case report Open
Background Marfan Syndrome (MS) is a connective tissue disorder, an autosomal dominant condition mostly caused by variants in the FBN1 gene, which encodes for fibrillin-1 protein. Anomalies in the gene lead to a wide variety of clinical ma…
View article: Comparison of 3D and 2D area measurement of acute burn wounds with LiDAR technique and deep learning model
Comparison of 3D and 2D area measurement of acute burn wounds with LiDAR technique and deep learning model Open
It is generally understood that wound areas appear smaller when calculated using 2D images, but the factors contributing to this discrepancy are not well-defined. With the rise of 3D photography, 3D segmentation, and 3D measurement, more a…
View article: Early prediction of mortality upon intensive care unit admission
Early prediction of mortality upon intensive care unit admission Open
Background We aimed to develop and validate models for predicting intensive care unit (ICU) mortality of critically ill adult patients as early as upon ICU admission. Methods Combined data of 79,657 admissions from two teaching hospitals’ …
View article: Signatures of lower respiratory tract microbiome in children with severe community-acquired pneumonia using shotgun metagenomic sequencing
Signatures of lower respiratory tract microbiome in children with severe community-acquired pneumonia using shotgun metagenomic sequencing Open
This study demonstrated that significantly different microbial community was associated with severity of community-acquired pneumonia requiring intensive care admission. Species-level shotgun metagenomic sequencing facilitates the explorat…
View article: Short- and medium-term cumulative effects of traffic-related air pollution on resting heart rate in the elderly: A wearable device study
Short- and medium-term cumulative effects of traffic-related air pollution on resting heart rate in the elderly: A wearable device study Open
Prolonged exposure to traffic-related air pollution results in cumulative cardiovascular risks, persisting for up to 50 days. These effects are more pronounced on warmer days and in individuals with chronic conditions or inactive lifestyle…
View article: Psychomotor Symptoms, Cognitive Impairments, and Suicidal Thoughts after COVID-19 Infection: A Case Report and Possible Allostatic Mechanism
Psychomotor Symptoms, Cognitive Impairments, and Suicidal Thoughts after COVID-19 Infection: A Case Report and Possible Allostatic Mechanism Open
Although neuropsychiatric manifestations are common in survivors of coronavirus disease 2019 (COVID-19), the pathophysiology is not yet elucidated. Here we describe the case of a geriatric inpatient who developed post-COVID depression with…
View article: Axial length, more than aging, decreases the thickness and superficial vessel density of retinal nerve fiber layer in non-glaucomatous eyes
Axial length, more than aging, decreases the thickness and superficial vessel density of retinal nerve fiber layer in non-glaucomatous eyes Open
Purpose This study seeks to build a normative database for the vessel density of the superficial retina (SVD) and evaluate how changes and trends in the retinal microvasculature may be influenced by age and axial length (AL) in non-glaucom…
View article: Real-Time Multiple Human Height Measurements With Occlusion Handling Using LiDAR and Camera of a Mobile Device
Real-Time Multiple Human Height Measurements With Occlusion Handling Using LiDAR and Camera of a Mobile Device Open
The measurement of height is a crucial indicator for assessing health and making informed decisions in various fields. Using a depth camera for height measurement has become popular due to its convenience and efficiency, as it does not req…
View article: P202: Post-COVID syndrome presented with psychomotor change and suicidal ideations: a geriatric case report
P202: Post-COVID syndrome presented with psychomotor change and suicidal ideations: a geriatric case report Open
Background: COVID-19 is notorious for its neuropsychiatric sequelae. Some patients present with anosmia and cognitive and attention deficits, also known as “brain-fog”. In COVID-19 survivors, psychiatric manifestations such as depression, …
View article: Enhancing panic disorder treatment with mobile-aided case management: an exploratory study based on a 3-year cohort analysis
Enhancing panic disorder treatment with mobile-aided case management: an exploratory study based on a 3-year cohort analysis Open
Background Individuals with panic disorder frequently face ongoing symptoms, suboptimal treatment adherence, and increased relapse rates. Although mobile health interventions have shown promise in improving treatment outcomes for numerous …
View article: Individual susceptibility to the acute impact of air pollution on resting heart rate among the elderly
Individual susceptibility to the acute impact of air pollution on resting heart rate among the elderly Open
View article: Outcomes of pediatric community‐acquired pneumonia before and after national pneumococcal immunization in Taiwan
Outcomes of pediatric community‐acquired pneumonia before and after national pneumococcal immunization in Taiwan Open
Objective In Taiwan, the incidence of invasive pneumococcal disease (IPD) in children declined after the catch‐up primary vaccination programs and the full national immunization program (NIP) with PCV13. The objective of the study was to i…
View article: Evaluating the Potential of Machine Learning and Wearable Devices in End-of-Life Care in Predicting 7-Day Death Events Among Patients With Terminal Cancer: Cohort Study
Evaluating the Potential of Machine Learning and Wearable Devices in End-of-Life Care in Predicting 7-Day Death Events Among Patients With Terminal Cancer: Cohort Study Open
Background An accurate prediction of mortality in end-of-life care is crucial but presents challenges. Existing prognostic tools demonstrate moderate performance in predicting survival across various time frames, primarily in in-hospital s…
View article: Applying a Smartwatch to Predict Work-related Fatigue for Emergency Healthcare Professionals: Machine Learning Method
Applying a Smartwatch to Predict Work-related Fatigue for Emergency Healthcare Professionals: Machine Learning Method Open
By using features derived from a smartwatch, we successfully built ML models capable of classifying the risk of work-related fatigue in the ED. By collecting more data to optimize the models, it should be possible to use smartwatch-based M…
View article: A dual-purpose deep learning model for auscultated lung and tracheal sound analysis based on mixed set training
A dual-purpose deep learning model for auscultated lung and tracheal sound analysis based on mixed set training Open
Many deep learning–based computerized respiratory sound analysis methods have previously been developed. However, these studies focus on either lung sound only or tracheal sound only. The effectiveness of using a lung sound analysis algori…
View article: Prognostic Value of Pace Variability, a Novel 6MWT-Derived Feature, in Patients with Chronic Obstructive Pulmonary Disease
Prognostic Value of Pace Variability, a Novel 6MWT-Derived Feature, in Patients with Chronic Obstructive Pulmonary Disease Open
Patients with COPD who exhibited greater pace variability during the 6MWT had a significantly higher risk of overall mortality and COPD-related hospitalizations, indicating a worse prognosis.
View article: Clinical characteristics of hospitalized children with community-acquired pneumonia and respiratory infections: Using machine learning approaches to support pathogen prediction at admission
Clinical characteristics of hospitalized children with community-acquired pneumonia and respiratory infections: Using machine learning approaches to support pathogen prediction at admission Open
We demonstrate how artificial intelligence can assist clinicians identify potential pathogens associated with pediatric ARIs upon admission. Our models provide explainable results that could help optimize the use of diagnostic testing. Int…
View article: Automatic segmentation and measurement of pressure injuries using deep learning models and a LiDAR camera
Automatic segmentation and measurement of pressure injuries using deep learning models and a LiDAR camera Open
View article: Use of multimodal dataset in AI for detecting glaucoma based on fundus photographs assessed with OCT: focus group study on high prevalence of myopia
Use of multimodal dataset in AI for detecting glaucoma based on fundus photographs assessed with OCT: focus group study on high prevalence of myopia Open
Background Glaucoma is one of the major causes of blindness; it is estimated that over 110 million people will be affected by glaucoma worldwide by 2040. Research on glaucoma detection using deep learning technology has been increasing, bu…
View article: Training a Deep Contextualized Language Model for International Classification of Diseases, 10th Revision Classification via Federated Learning: Model Development and Validation Study
Training a Deep Contextualized Language Model for International Classification of Diseases, 10th Revision Classification via Federated Learning: Model Development and Validation Study Open
Background The automatic coding of clinical text documents by using the International Classification of Diseases, 10th Revision (ICD-10) can be performed for statistical analyses and reimbursements. With the development of natural language…
View article: Fast Healthcare Interoperability Resources for Inpatient Deterioration Detection With Time-Series Vital Signs: Design and Implementation Study
Fast Healthcare Interoperability Resources for Inpatient Deterioration Detection With Time-Series Vital Signs: Design and Implementation Study Open
Background Vital signs have been widely adopted in in-hospital cardiac arrest (IHCA) assessment, which plays an important role in inpatient deterioration detection. As the number of early warning systems and artificial intelligence applica…
View article: Fast Healthcare Interoperability Resources (FHIR) for Inpatient Deterioration Detection with Time-Series Vital Signs: A Design and Implementation Study (Preprint)
Fast Healthcare Interoperability Resources (FHIR) for Inpatient Deterioration Detection with Time-Series Vital Signs: A Design and Implementation Study (Preprint) Open
BACKGROUND Vital signs have been widely adopted in in-hospital cardiac arrest (IHCA) assessment, which plays an important role in inpatient deterioration detection. As the number of early warning systems and artificial intelligence applic…
View article: Diagnosis of a Single-Nucleotide Variant in Whole-Exome Sequencing Data for Patients With Inherited Diseases: Machine Learning Study Using Artificial Intelligence Variant Prioritization
Diagnosis of a Single-Nucleotide Variant in Whole-Exome Sequencing Data for Patients With Inherited Diseases: Machine Learning Study Using Artificial Intelligence Variant Prioritization Open
Background In recent years, thanks to the rapid development of next-generation sequencing (NGS) technology, an entire human genome can be sequenced in a short period. As a result, NGS technology is now being widely introduced into clinical…
View article: Combining attention with spectrum to handle missing values on time series data without imputation
Combining attention with spectrum to handle missing values on time series data without imputation Open
In the development of predictive models, the problem of missing data is a critical issue that traditionally requires a two-step analysis. Data scientists analyze the patterns of missing values, select variables, impute missing values on th…
View article: A Progressively Expanded Database for Automated Lung Sound Analysis: An Update
A Progressively Expanded Database for Automated Lung Sound Analysis: An Update Open
We previously established an open-access lung sound database, HF_Lung_V1, and developed deep learning models for inhalation, exhalation, continuous adventitious sound (CAS), and discontinuous adventitious sound (DAS) detection. The amount …