AIMC Topic: Middle Aged

Clear Filters Showing 1751 to 1760 of 17155 articles

Deep learning for differential diagnosis of parotid tumors based on 2.5D magnetic resonance imaging.

Annals of medicine
PURPOSE: Accurate preoperative diagnosis of parotid gland tumors (PGTs) is crucial for surgical planning since malignant tumors require more extensive excision. Though fine-needle aspiration biopsy is the diagnostic gold standard, its sensitivity in ...

Development and validation of a machine learning model to predict cognitive behavioral therapy outcome in obsessive-compulsive disorder using clinical and neuroimaging data.

Journal of affective disorders
BACKGROUND: Cognitive behavioral therapy (CBT) is a first-line treatment for obsessive-compulsive disorder (OCD), but clinical response is difficult to predict. In this study, we aimed to develop predictive models using clinical and neuroimaging data...

Morphological characterization of median nerve and transverse carpal ligament from ultrasound images using convolutional neural networks.

Medical engineering & physics
OBJECTIVES: The purpose of this study was to automatically segment and quantify the median nerve and carpal arch from ultrasound images using convolutional neural network (CNN).

Your turn: At home turning angle estimation for Parkinson's disease severity assessment.

Artificial intelligence in medicine
People with Parkinson's Disease (PD) often experience progressively worsening gait, including changes in how they turn around, as the disease progresses. Existing clinical rating tools are not capable of capturing hour-by-hour variations of PD sympto...

Multi-datasets transfer multitask learning for simultaneous blood glucose and blood pressure monitoring using common PPG features.

Computers in biology and medicine
The simultaneous monitoring of both blood glucose level (BGL) and blood pressure (BP) has rarely been studied directly. The exploitation of physiological interactions between them will advance the learning of either task. However, the lack of availab...

Deep learning model using CT images for longitudinal prediction of benign and malignant ground-glass nodules.

European journal of radiology
OBJECTIVES: To develop and validate a CT image-based multiple time-series deep learning model for the longitudinal prediction of benign and malignant pulmonary ground-glass nodules (GGNs).

Multimodal deep learning for predicting unsuccessful recanalization in refractory large vessel occlusion.

European journal of radiology
PURPOSE: This study explores a multi-modal deep learning approach that integrates pre-intervention neuroimaging and clinical data to predict endovascular therapy (EVT) outcomes in acute ischemic stroke patients. To this end, consecutive stroke patien...

Radiogenomic insights suggest that multiscale tumor heterogeneity is associated with interpretable radiomic features and outcomes in cancer patients.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
BACKGROUND: To develop radiogenomic subtypes and determine the relationships between radiomic phenotypes and multiomics molecular characteristics.

Machine learning to predict mitochondrial diseases by phenotypes.

Mitochondrion
Diagnosing mitochondrial diseases remains challenging because of the heterogeneous symptoms. This study aims to use machine learning to predict mitochondrial diseases from phenotypes to reduce genetic testing costs. This study included patients who u...

Neural mechanisms underlying the improvement of gait disturbances in stroke patients through robot-assisted gait training based on QEEG and fNIRS: a randomized controlled study.

Journal of neuroengineering and rehabilitation
BACKGROUND: Robot-assisted gait training is more effective in improving lower limb function and walking ability in stroke patients compared to conventional rehabilitation, but the neural mechanisms remain unclear. This study aims to explore the effec...