AIMC Topic: Aged

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Forecasting Retinal Nerve Fiber Layer Thickness from Multimodal Temporal Data Incorporating OCT Volumes.

Ophthalmology. Glaucoma
PURPOSE: The purpose of this study was to develop a machine learning model to forecast future circumpapillary retinal nerve fiber layer (cpRNFL) thickness in eyes of healthy, glaucoma suspect, and glaucoma participants from multimodal temporal data.

Predictive Utility of a Machine Learning Algorithm in Estimating Mortality Risk in Cardiac Surgery.

The Annals of thoracic surgery
BACKGROUND: This study evaluated the predictive utility of a machine learning algorithm in estimating operative mortality risk in cardiac surgery.

Surgical experience of using the endoscope manipulator robot EMARO in totally extraperitoneal inguinal hernia repair: A case report.

Asian journal of endoscopic surgery
Robot-assisted surgery has advanced rapidly since the 1980s. However, new equipment is still needed to overcome problems in conventional endoscopic surgery, including unique risks, such as camera shake and communication difficulties between the opera...

Computer-assisted assessment of colonic polyp histopathology using probe-based confocal laser endomicroscopy.

International journal of colorectal disease
INTRODUCTION: Probe-based confocal laser endomicroscopy (pCLE) is a promising modality for classifying polyp histology in vivo, but decision making in real-time is hampered by high-magnification targeting and by the learning curve for image interpret...

Fall Risk Prediction in Multiple Sclerosis Using Postural Sway Measures: A Machine Learning Approach.

Scientific reports
Numerous postural sway metrics have been shown to be sensitive to balance impairment and fall risk in individuals with MS. Yet, there are no guidelines concerning the most appropriate postural sway metrics to monitor impairment. This investigation im...

Improved detection of Parkinsonian resting tremor with feature engineering and Kalman filtering.

Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
OBJECTIVE: Accurate and reliable detection of tremor onset in Parkinson's disease (PD) is critical to the success of adaptive deep brain stimulation (aDBS) therapy. Here, we investigated the potential use of feature engineering and machine learning m...

Quantitative susceptibility mapping based hybrid feature extraction for diagnosis of Parkinson's disease.

NeuroImage. Clinical
Parkinson's disease is the second most common neurodegenerative disease in the elderly after Alzheimer's disease. The aetiology and pathogenesis of Parkinson's disease (PD) are still unclear, but the loss of dopaminergic cells and the excessive iron ...