AIMC Topic: Female

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Automatic GRBAS Scoring of Pathological Voices using Deep Learning and a Small Set of Labeled Voice Data.

Journal of voice : official journal of the Voice Foundation
OBJECTIVES: Auditory-perceptual evaluation frameworks, such as the grade-roughness-breathiness-asthenia-strain (GRBAS) scale, are the gold standard for the quantitative evaluation of pathological voice quality. However, the evaluation is subjective; ...

Detection of Neurogenic Voice Disorders Using the Fisher Vector Representation of Cepstral Features.

Journal of voice : official journal of the Voice Foundation
Neurogenic voice disorders (NVDs) are caused by damage or malfunction of the central or peripheral nervous system that controls vocal fold movement. In this paper, we investigate the potential of the Fisher vector (FV) encoding in automatic detection...

Determinants of ascending aortic morphology: cross-sectional deep learning-based analysis on 25 073 non-contrast-enhanced NAKO MRI studies.

European heart journal. Cardiovascular Imaging
AIMS: Understanding determinants of thoracic aortic morphology is crucial for precise diagnostics and therapeutic approaches. This study aimed to automatically characterize ascending aortic morphology based on 3D non-contrast-enhanced magnetic resona...

A quantitative analysis of symmetry on standard anteroposterior pelvic X-ray.

Acta orthopaedica et traumatologica turcica
Objective: A pelvic X-ray examination might not be accomplished accurately if the images are not acquired properly. In this study, the aim was to develop an automated model using artificial intelligence capable of accurately quantifying the symmetry ...

Machine learning algorithms reveal gut microbiota signatures associated with chronic hepatitis B-related hepatic fibrosis.

World journal of gastroenterology
BACKGROUND: Hepatic fibrosis (HF) represents a pivotal stage in the progression and potential reversal of cirrhosis, underscoring the importance of early identification and therapeutic intervention to modulate disease trajectory.

[Serum proteomics and machine learning unveil new diagnostic biomarkers for tuberculosis in adolescents and young adults].

Sheng wu gong cheng xue bao = Chinese journal of biotechnology
Adolescents and young adults (AYAs) are one of the major populations susceptible to tuberculosis. However, little is known about the unique characteristics and diagnostic biomarkers of tuberculosis in this population. In this study, 81 AYAs were recr...

Applying Machine Learning to Gait Analysis Data for Hip Osteoarthritis Diagnosis.

Studies in health technology and informatics
BACKGROUND: Hip osteoarthritis (OA) is a degenerative joint disease that affects approximately 25% of individuals over their lifetime, with prevalence expected to rise due to population aging. Gait analysis is recognized as a valuable tool for unders...

Using a Logic Model to Explore Seniors' Interactions with a Coaching Robot.

Studies in health technology and informatics
BACKGROUND: The use of Logic Models provides a structured approach to understanding and visualizing the impact of interventions in complex systems, such as Ambient or Active Assisted Living (AAL).

A Machine Learning-Based Risk Assessment Model for Poor Postoperative Pain Outcome.

Studies in health technology and informatics
Postoperative pain is a relevant and unresolved problem in clinical practice. In order to reduce the occurrence of severe postoperative pain, preventive, multi-professional and target group-specific pain management should be implemented. Risk assessm...

Classifying Type 2 Diabetes Using N-Glycan Profiling and Machine Learning Algorithms.

Studies in health technology and informatics
BACKGROUND: Type 2 diabetes (T2D) continues to present a global public health challenge due to its increasing prevalence. Early diagnosis is critical for preventing complications, but current screening methods often fail to detect early diabetic cond...