AIMC Topic: Young Adult
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Toward Precision Diagnosis: Machine Learning in Identifying Malignant Orbital Tumors With Multiparametric 3 T MRI.
Investigative radiology
Apr 11, 2024
BACKGROUND: Orbital tumors present a diagnostic challenge due to their varied locations and histopathological differences. Although recent advancements in imaging have improved diagnosis, classification remains a challenge. The integration of artific...
Impact of COVID-19 on arthritis with generative AI.
International immunopharmacology
Apr 11, 2024
OBJECTIVE: The study aims to examine the effects of the COVID-19 pandemic on the prevalence of arthritis in the US using a specific generative AI tool.
Artificial intelligence for detection of effusion and lipo-hemarthrosis in X-rays and CT of the knee.
European journal of radiology
Apr 10, 2024
BACKGROUND: Traumatic knee injuries are challenging to diagnose accurately through radiography and to a lesser extent, through CT, with fractures sometimes overlooked. Ancillary signs like joint effusion or lipo-hemarthrosis are indicative of fractur...
Exudates and Transudates
Knee Injuries
Humans
Hemarthrosis
Artificial Intelligence
Middle Aged
Algorithms
Adolescent
Retrospective Studies
Radiographic Image Interpretation, Computer-Assisted
Tomography, X-Ray Computed
Knee Joint
Female
Aged
Young Adult
Aged, 80 and over
Adult
Sensitivity and Specificity
Male
Intelligent classification of major depressive disorder using rs-fMRI of the posterior cingulate cortex.
Journal of affective disorders
Apr 9, 2024
Major Depressive Disorder (MDD) is a widespread psychiatric condition that affects a significant portion of the global population. The classification and diagnosis of MDD is crucial for effective treatment. Traditional methods, based on clinical asse...
Predicting post-treatment symptom severity for adults receiving psychological therapy in routine care for generalised anxiety disorder: a machine learning approach.
Psychiatry research
Apr 9, 2024
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)
Apr 9, 2024
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)
Apr 9, 2024
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
Apr 9, 2024
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)
Apr 7, 2024
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
Apr 6, 2024
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.
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