AIMC Topic: Aged

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Accurate Patient-Specific Machine Learning Models of Glioblastoma Invasion Using Transfer Learning.

AJNR. American journal of neuroradiology
BACKGROUND AND PURPOSE: MR imaging-based modeling of tumor cell density can substantially improve targeted treatment of glioblastoma. Unfortunately, interpatient variability limits the predictive ability of many modeling approaches. We present a tran...

Natural language processing and machine learning algorithm to identify brain MRI reports with acute ischemic stroke.

PloS one
BACKGROUND AND PURPOSE: This project assessed performance of natural language processing (NLP) and machine learning (ML) algorithms for classification of brain MRI radiology reports into acute ischemic stroke (AIS) and non-AIS phenotypes.

Machine learning-based prediction of heart failure readmission or death: implications of choosing the right model and the right metrics.

ESC heart failure
AIMS: Machine learning (ML) is widely believed to be able to learn complex hidden interactions from the data and has the potential in predicting events such as heart failure (HF) readmission and death. Recent studies have revealed conflicting results...

Detection of mild cognitive impairment in a community-dwelling population using quantitative, multiparametric MRI-based classification.

Human brain mapping
Early and accurate mild cognitive impairment (MCI) detection within a heterogeneous, nonclinical population is needed to improve care for persons at risk of developing dementia. Magnetic resonance imaging (MRI)-based classification may aid early diag...

Accuracy of ultrawide-field fundus ophthalmoscopy-assisted deep learning for detecting treatment-naïve proliferative diabetic retinopathy.

International ophthalmology
PURPOSE: We investigated using ultrawide-field fundus images with a deep convolutional neural network (DCNN), which is a machine learning technology, to detect treatment-naïve proliferative diabetic retinopathy (PDR).

Upper limb motor pre-clinical assessment in Parkinson's disease using machine learning.

Parkinsonism & related disorders
INTRODUCTION: Parkinson's disease (PD) is a common neurodegenerative disorder characterized by disabling motor and non-motor symptoms. For example, idiopathic hyposmia (IH), which is a reduced olfactory sensitivity, is typical in >95% of PD patients ...

Hybrid multivariate pattern analysis combined with extreme learning machine for Alzheimer's dementia diagnosis using multi-measure rs-fMRI spatial patterns.

PloS one
BACKGROUND: Early diagnosis of Alzheimer's disease (AD) and Mild Cognitive Impairment (MCI) is essential for timely treatment. Machine learning and multivariate pattern analysis (MVPA) for the diagnosis of brain disorders are explicitly attracting at...

Use of a robotic camera holder (FreeHand) for laparoscopic appendicectomy.

Minimally invasive therapy & allied technologies : MITAT : official journal of the Society for Minimally Invasive Therapy
Use of a mechanical arm to hold the laparoscopic camera has many advantages. FreeHand (FreeHand Ltd, Guildford, United Kingdom) is a robotic camera holder which uses head movement and infrared technology. This trial assessed the usefulness of FreeHa...

A deep learning approach for real-time detection of sleep spindles.

Journal of neural engineering
OBJECTIVE: Sleep spindles have been implicated in memory consolidation and synaptic plasticity during NREM sleep. Detection accuracy and latency in automatic spindle detection are critical for real-time applications.