AIMC Topic: Young Adult

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Predicting post-treatment symptom severity for adults receiving psychological therapy in routine care for generalised anxiety disorder: a machine learning approach.

Psychiatry research
Approximately half of generalised anxiety disorder (GAD) patients do not recover from first-line treatments, and no validated prediction models exist to inform individuals or clinicians of potential treatment benefits. This study aimed to develop and...

IMU-Based Real-Time Estimation of Gait Phase Using Multi-Resolution Neural Networks.

Sensors (Basel, Switzerland)
This work presents a real-time gait phase estimator using thigh- and shank-mounted inertial measurement units (IMUs). A multi-rate convolutional neural network (CNN) was trained to estimate gait phase for a dataset of 16 participants walking on an in...

Evaluation of Hand Action Classification Performance Using Machine Learning Based on Signals from Two sEMG Electrodes.

Sensors (Basel, Switzerland)
Classification-based myoelectric control has attracted significant interest in recent years, leading to prosthetic hands with advanced functionality, such as multi-grip hands. Thus far, high classification accuracies have been achieved by increasing ...

Validation of Machine Learning-Based Assessment of Major Depressive Disorder from Paralinguistic Speech Characteristics in Routine Care.

Depression and anxiety
New developments in machine learning-based analysis of speech can be hypothesized to facilitate the long-term monitoring of major depressive disorder (MDD) during and after treatment. To test this hypothesis, we collected 550 speech samples from tele...

Development of a deep-learning algorithm for age estimation on CT images of the vertebral column.

Legal medicine (Tokyo, Japan)
PURPOSE: The accurate age estimation of cadavers is essential for their identification. However, conventional methods fail to yield adequate age estimation especially in elderly cadavers. We developed a deep learning algorithm for age estimation on C...

Assessing the Influence of B-US, CDFI, SE, and Patient Age on Predicting Molecular Subtypes in Breast Lesions Using Deep Learning Algorithms.

Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine
OBJECTIVES: Our study aims to investigate the impact of B-mode ultrasound (B-US) imaging, color Doppler flow imaging (CDFI), strain elastography (SE), and patient age on the prediction of molecular subtypes in breast lesions.

Development and validation of machine learning models to predict postoperative infarction in moyamoya disease.

Journal of neurosurgery
OBJECTIVE: Cerebral infarction is a common complication in patients undergoing revascularization surgery for moyamoya disease (MMD). Although previous statistical evaluations have identified several risk factors for postoperative brain ischemia, the ...

Deep learning denoising reconstruction enables faster T2-weighted FLAIR sequence acquisition with satisfactory image quality.

Journal of medical imaging and radiation oncology
INTRODUCTION: Deep learning reconstruction (DLR) technologies are the latest methods attempting to solve the enduring problem of reducing MRI acquisition times without compromising image quality. The clinical utility of this reconstruction technique ...

Vaginal microbiota molecular profiling and diagnostic performance of artificial intelligence-assisted multiplex PCR testing in women with bacterial vaginosis: a single-center experience.

Frontiers in cellular and infection microbiology
BACKGROUND: Bacterial vaginosis (BV) is a most common microbiological syndrome. The use of molecular methods, such as multiplex real-time PCR (mPCR) and next-generation sequencing, has revolutionized our understanding of microbial communities. Here, ...

Identification of the best machine learning model for the prediction of driver injury severity.

International journal of injury control and safety promotion
Predicting the injury severities sustained by drivers engaged in road traffic accidents is a key topic of research in road traffic safety. The current study analyzed the driver injury severity (DIS) using twelve machine learning (ML) algorithms. Thes...