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Instance-Based Representation Using Multiple Kernel Learning for Predicting Conversion to Alzheimer Disease.

International journal of neural systems
The early detection of Alzheimer's disease and quantification of its progression poses multiple difficulties for machine learning algorithms. Two of the most relevant issues are related to missing data and results interpretability. To deal with both ...

Machine learning reveals chronic graft--host disease phenotypes and stratifies survival after stem cell transplant for hematologic malignancies.

Haematologica
The application of machine learning in medicine has been productive in multiple fields, but has not previously been applied to analyze the complexity of organ involvement by chronic graft--host disease. Chronic graft--host disease is classified by an...

Adapting artificial neural networks to a specific driver enhances detection and prediction of drowsiness.

Accident; analysis and prevention
Monitoring car drivers for drowsiness is crucial but challenging. The high inter-individual variability observed in measurements raises questions about the accuracy of the drowsiness detection process. In this study, we sought to enhance the performa...

Implementation of deep neural networks to count dopamine neurons in substantia nigra.

The European journal of neuroscience
Unbiased estimates of neuron numbers within substantia nigra are crucial for experimental Parkinson's disease models and gene-function studies. Unbiased stereological counting techniques with optical fractionation are successfully implemented, but ar...

Deep learning-based quantification of abdominal fat on magnetic resonance images.

PloS one
Obesity is increasingly prevalent and associated with increased risk of developing type 2 diabetes, cardiovascular diseases, and cancer. Magnetic resonance imaging (MRI) is an accurate method for determination of body fat volume and distribution. How...

MRI-based automated detection of implanted low dose rate (LDR) brachytherapy seeds using quantitative susceptibility mapping (QSM) and unsupervised machine learning (ML).

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
BACKGROUND AND PURPOSE: Permanent seed brachytherapy is an established treatment option for localized prostate cancer. Currently, post-implant dosimetry is performed on CT images despite challenging target delineation due to limited soft tissue contr...

Comfort and Attitudes Towards Robots Among Young, Middle-Aged, and Older Adults: A Cross-Sectional Study.

Journal of nursing scholarship : an official publication of Sigma Theta Tau International Honor Society of Nursing
PURPOSE: To explore the social impact of, comfort with, and negative attitudes towards robots among young, middle-aged, and older adults in the United States.

A Continuously Updated, Computationally Efficient Stress Recognition Framework Using Electroencephalogram (EEG) by Applying Online Multitask Learning Algorithms (OMTL).

IEEE journal of biomedical and health informatics
Recognizing the factors that cause stress is a crucial step toward early detection of stressors. In this regard, several studies make an effort to recognize individuals' stress using an Electroencephalogram (EEG). However, current EEG-based stress re...

Experience With Hypothermic Machine Perfusion in Expanded Criteria Donors: Functional Outcomes.

Transplantation proceedings
UNLABELLED: Hypothermic machine perfusion (HMP) decreases delayed graft function (DGF) and improves 1-year graft survival in expanded criteria donors (ECDs). Time of HMP could be associated with incidence of DGF.