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A multilevel-ROI-features-based machine learning method for detection of morphometric biomarkers in Parkinson's disease.

Neuroscience letters
Machine learning methods have been widely used in recent years for detection of neuroimaging biomarkers in regions of interest (ROIs) and assisting diagnosis of neurodegenerative diseases. The innovation of this study is to use multilevel-ROI-feature...

In-Situ Force Augmentation Improves Surface Contact and Force Control.

IEEE transactions on haptics
Surgeons routinely perform surgery with noisy, sub-threshold, or obscured visual and haptic feedback, either due to the necessary surgical approach, or because the systems on which they are operating are exceedingly delicate. Technological solutions ...

Machine Learning for Social Services: A Study of Prenatal Case Management in Illinois.

American journal of public health
OBJECTIVES: To evaluate the positive predictive value of machine learning algorithms for early assessment of adverse birth risk among pregnant women as a means of improving the allocation of social services.

Metastasis detection from whole slide images using local features and random forests.

Cytometry. Part A : the journal of the International Society for Analytical Cytology
Digital pathology has led to a demand for automated detection of regions of interest, such as cancerous tissue, from scanned whole slide images. With accurate methods using image analysis and machine learning, significant speed-up, and savings in cos...

An In-home Advanced Robotic System to Manage Elderly Home-care Patients' Medications: A Pilot Safety and Usability Study.

Clinical therapeutics
PURPOSE: We examined the safety profile and usability of an integrated advanced robotic device and telecare system to promote medication adherence for elderly home-care patients.

Evaluation of machine learning algorithms and structural features for optimal MRI-based diagnostic prediction in psychosis.

PloS one
A relatively large number of studies have investigated the power of structural magnetic resonance imaging (sMRI) data to discriminate patients with schizophrenia from healthy controls. However, very few of them have also included patients with bipola...

Two-phase deep convolutional neural network for reducing class skewness in histopathological images based breast cancer detection.

Computers in biology and medicine
Different types of breast cancer are affecting lives of women across the world. Common types include Ductal carcinoma in situ (DCIS), Invasive ductal carcinoma (IDC), Tubular carcinoma, Medullary carcinoma, and Invasive lobular carcinoma (ILC). While...

Use of Machine Learning Classifiers and Sensor Data to Detect Neurological Deficit in Stroke Patients.

Journal of medical Internet research
BACKGROUND: The pronator drift test (PDT), a neurological examination, is widely used in clinics to measure motor weakness of stroke patients.

EEG-Based Computer Aided Diagnosis of Autism Spectrum Disorder Using Wavelet, Entropy, and ANN.

BioMed research international
Autism spectrum disorder (ASD) is a type of neurodevelopmental disorder with core impairments in the social relationships, communication, imagination, or flexibility of thought and restricted repertoire of activity and interest. In this work, a new c...