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Predicting one-year outcome in first episode psychosis using machine learning.

PloS one
BACKGROUND: Early illness course correlates with long-term outcome in psychosis. Accurate prediction could allow more focused intervention. Earlier intervention corresponds to significantly better symptomatic and functional outcomes. Our study object...

Impact of nominal photon energies on normal tissue sparing in knowledge-based radiotherapy treatment planning for rectal cancer patients.

PloS one
The interactive adjustment of the optimization objectives during the treatment planning process has made it difficult to evaluate the impact of beam quality exclusively in radiotherapy. Without consensus in the published results, the arbitrary select...

Identifying Features that Enhance Older Adults' Acceptance of Robots: A Mixed Methods Study.

Gerontology
BACKGROUND: With global aging, robots are considered a promising solution for handling the shortage of aged care and companionships. However, these technologies would serve little purpose if their intended users do not accept them. While the socioemo...

A deep learning framework for efficient analysis of breast volume and fibroglandular tissue using MR data with strong artifacts.

International journal of computer assisted radiology and surgery
PURPOSE: The main purpose of this work is to develop, apply, and evaluate an efficient approach for breast density estimation in magnetic resonance imaging data, which contain strong artifacts including intensity inhomogeneities.

A Deep Learning System for Automated Angle-Closure Detection in Anterior Segment Optical Coherence Tomography Images.

American journal of ophthalmology
PURPOSE: Anterior segment optical coherence tomography (AS-OCT) provides an objective imaging modality for visually identifying anterior segment structures. An automated detection system could assist ophthalmologists in interpreting AS-OCT images for...

The trauma severity model: An ensemble machine learning approach to risk prediction.

Computers in biology and medicine
Statistical theory indicates that a flexible model can attain a lower generalization error than an inflexible model, provided that the setting is appropriate. This is highly relevant for mortality risk prediction with trauma patients, as researchers ...

SPINNE: An app for human vertebral height estimation based on artificial neural networks.

Forensic science international
The absence or poor preservation of vertebrae often prevent the application of the anatomical method for stature estimation. The main objective of this paper was to develop a web app based on artificial neural network (ANN) models to estimate the ver...

Detection of chromosome structural variation by targeted next-generation sequencing and a deep learning application.

Scientific reports
Molecular testing is increasingly important in cancer diagnosis. Targeted next generation sequencing (NGS) is widely accepted method but structural variation (SV) detection by targeted NGS remains challenging. In the brain tumor, identification of mo...

Predictive markers for Parkinson's disease using deep neural nets on neuromelanin sensitive MRI.

NeuroImage. Clinical
Neuromelanin sensitive magnetic resonance imaging (NMS-MRI) has been crucial in identifying abnormalities in the substantia nigra pars compacta (SNc) in Parkinson's disease (PD) as PD is characterized by loss of dopaminergic neurons in the SNc. Curre...