AIMC Topic: Aged

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Development of an unsupervised machine learning algorithm for the prognostication of walking ability in spinal cord injury patients.

The spine journal : official journal of the North American Spine Society
BACKGROUND CONTEXT: Traumatic spinal cord injury can have a dramatic effect on a patient's life. The degree of neurologic recovery greatly influences a patient's treatment and expected quality of life. This has resulted in the development of machine ...

Preoperative Prediction of Pancreatic Neuroendocrine Neoplasms Grading Based on Enhanced Computed Tomography Imaging: Validation of Deep Learning with a Convolutional Neural Network.

Neuroendocrinology
INTRODUCTION: The pathological grading of pancreatic neuroendocrine neoplasms (pNENs) is an independent predictor of survival and indicator for treatment. Deep learning (DL) with a convolutional neural network (CNN) may improve the preoperative predi...

Artificial neural network analysis of the oxygen saturation signal enables accurate diagnostics of sleep apnea.

Scientific reports
The severity of obstructive sleep apnea (OSA) is classified using apnea-hypopnea index (AHI). Accurate determination of AHI currently requires manual analysis and complicated registration setup making it expensive and labor intensive. Partially for t...

Sex estimation from sacrum and coccyx with discriminant analyses and neural networks in an equally distributed population by age and sex.

Forensic science international
Sex estimation is an essential step in the process of the identification of the skeletal remains in forensic anthropology since it reduces the number of possible matches by half. In this study, sex estimation with 21 sacral and coccygeal metric param...

Using supervised learning machine algorithm to identify future fallers based on gait patterns: A two-year longitudinal study.

Experimental gerontology
INTRODUCTION: Given their major health consequences in the elderly, identifying people at risk of fall is a major challenge faced by clinicians. A lot of studies have confirmed the relationships between gait parameters and falls incidence. However, a...

Quantifying brain metabolism from FDG-PET images into a probability of Alzheimer's dementia score.

Human brain mapping
F-fluorodeoxyglucose positron emission tomography (FDG-PET) enables in-vivo capture of the topographic metabolism patterns in the brain. These images have shown great promise in revealing the altered metabolism patterns in Alzheimer's disease (AD). ...

A validated natural language processing algorithm for brain imaging phenotypes from radiology reports in UK electronic health records.

BMC medical informatics and decision making
BACKGROUND: Manual coding of phenotypes in brain radiology reports is time consuming. We developed a natural language processing (NLP) algorithm to enable automatic identification of brain imaging in radiology reports performed in routine clinical pr...

External validation of the SORG 90-day and 1-year machine learning algorithms for survival in spinal metastatic disease.

The spine journal : official journal of the North American Spine Society
BACKGROUND CONTEXT: Preoperative survival estimation in spinal metastatic disease helps determine the appropriateness of invasive management. The SORG ML 90-day and 1-year machine learning algorithms for survival in spinal metastatic disease were pre...