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Deep learning models for predicting hearing thresholds based on joint stimulus-frequency otoacoustic emissions and distortion-product otoacoustic emissions.
Hearing research
Jun 29, 2025
According to the dual-source generation hypothesis, stimulus-frequency otoacoustic emissions (SFOAEs) and distortion-product OAEs (DPOAEs) arise from different cochlear mechanisms, and both are capable of characterizing hearing loss. However, their j...
Hearing
Auditory Threshold
Cochlea
Otoacoustic Emissions, Spontaneous
Predictive Value of Tests
Case-Control Studies
Hearing Loss, Sensorineural
Humans
Signal Processing, Computer-Assisted
Acoustic Stimulation
Deep Learning
Neural Networks, Computer
Audiometry, Pure-Tone
Young Adult
Adolescent
Female
Adult
Reproducibility of Results
Male
Aged
Middle Aged
A novel speech signal feature extraction technique to detect speech impairment in children accurately.
Computers in biology and medicine
Jun 29, 2025
Speech signal processing and extracting useful information from speech signal is necessary for speech language impairment (SLI) detection in children. Although different features has been suggested for SLI detection, there is still a scope exist for ...
Exploring data augmentation methods to enhance EEG measures for epilepsy seizure detection.
Computers in biology and medicine
Jun 29, 2025
Automatic seizure detection using machine learning can reduce the workload of clinicians in epilepsy diagnosis. However, the class imbalance between seizure and non-seizure data limits model performance. Data augmentation offers a solution, yet few s...
Novel Artificial Intelligence-Driven Infant Meningitis Screening From High-Resolution Ultrasound Imaging.
Ultrasound in medicine & biology
Jun 29, 2025
BACKGROUND: Infant meningitis can be a life-threatening disease and requires prompt and accurate diagnosis to prevent severe outcomes or death. Gold-standard diagnosis requires lumbar puncture (LP) to obtain and analyze cerebrospinal fluid (CSF). Des...
Deep Learning-Based Automated Detection of the Middle Cerebral Artery in Transcranial Doppler Ultrasound Examinations.
Ultrasound in medicine & biology
Jun 29, 2025
OBJECTIVE: Transcranial Doppler (TCD) ultrasound has significant clinical value for assessing cerebral hemodynamics, but its reliance on operator expertise limits broader clinical adoption. In this work, we present a lightweight real-time deep learni...
Evaluation of meibomian gland dysfunction with deep learning model considering different datasets and gland morphology.
Computers in biology and medicine
Jun 28, 2025
Meibomian gland dysfunction (MGD) is recognized as the primary cause of evaporative-type dry eye disease (DED). Diagnosis typically involves assessing meibomian gland (MG) morphology alongside symptom evaluation. Traditionally, experts manually grade...
Classification of knee osteoarthritis severity using markerless motion capture and long short-term memory fully convolutional network.
Computers in biology and medicine
Jun 28, 2025
This study explored the integration of markerless motion capture and deep learning to classify knee osteoarthritis severity based on gait kinematics, providing an alternative to traditional assessment methods. We employed a Long Short-Term Memory Ful...
Early detection of Alzheimer's disease using small RNAs. Results from the EPAD cohort.
The journal of prevention of Alzheimer's disease
Jun 28, 2025
BACKGROUND: Alzheimer's disease (AD) is the most common form of dementia, and early diagnosis is crucial to enable effective interventions. Currently, Alzheimer's disease is diagnosed through cognitive assessments, brain imaging and fluid biomarkers ...
Predicting adolescents' environmental action: From individual to national-level factors using an explainable machine learning approach.
Journal of environmental management
Jun 28, 2025
As a key force in future environmental actions, youth play a crucial role in driving societal transformation. However, the factors influencing youth environmental actions have not been fully validated, and the role of national-level influences is oft...
The diagnostic model from semi-supervised cross modality transformation improved the distinguished ability of X-rays for pulmonary tuberculosis.
Clinical radiology
Jun 27, 2025
BACKGROUND: Early diagnosis of tuberculosis is particularly difficult in resource-poor areas. Traditional chest X-rays (CXR) have limited accuracy, while CT scans are costly and involve radiation exposure. The study aims to improve the diagnostic acc...
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