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Emerging Adults' Expectations About the Next Generation of Robots: Exploring Robotic Needs Through a Latent Profile Analysis.

Cyberpsychology, behavior and social networking
The investigation of emerging adults' expectations of development of the next generation of robots is a fundamental challenge to narrow the gap between expectations and real technological advances, which can potentially impact the effectiveness of fu...

Frontotemporal EEG to guide sedation in COVID-19 related acute respiratory distress syndrome.

Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
OBJECTIVE: To study if limited frontotemporal electroencephalogram (EEG) can guide sedation changes in highly infectious novel coronavirus disease 2019 (COVID-19) patients receiving neuromuscular blocking agent.

Clinical value of machine learning-based interpretation of I-123 FP-CIT scans to detect Parkinson's disease: a two-center study.

Annals of nuclear medicine
PURPOSE: Our aim was to develop and validate a machine learning (ML)-based approach for interpretation of I-123 FP-CIT SPECT scans to discriminate Parkinson's disease (PD) from non-PD and to determine its generalizability and clinical value in two ce...

Covid-19 Automated Diagnosis and Risk Assessment through Metabolomics and Machine Learning.

Analytical chemistry
COVID-19 is still placing a heavy health and financial burden worldwide. Impairment in patient screening and risk management plays a fundamental role on how governments and authorities are directing resources, planning reopening, as well as sanitary ...

Deep Learning Regression for Prostate Cancer Detection and Grading in Bi-Parametric MRI.

IEEE transactions on bio-medical engineering
One of the most common types of cancer in men is prostate cancer (PCa). Biopsies guided by bi-parametric magnetic resonance imaging (MRI) can aid PCa diagnosis. Previous works have mostly focused on either detection or classification of PCa from MRI....

Identifying intentional injuries among children and adolescents based on Machine Learning.

PloS one
BACKGROUND: Compared to other studies, the injury monitoring of Chinese children and adolescents has captured a low level of intentional injuries on account of self-harm/suicide and violent attacks. Intentional injuries in children and adolescents ha...

Preictal state detection using prodromal symptoms: A machine learning approach.

Epilepsia
A reliable identification of a high-risk state for upcoming seizures may allow for preemptive treatment and improve the quality of patients' lives. We evaluated the ability of prodromal symptoms to predict preictal states using a machine learning (ML...

A comparison of machine learning models versus clinical evaluation for mortality prediction in patients with sepsis.

PloS one
INTRODUCTION: Patients with sepsis who present to an emergency department (ED) have highly variable underlying disease severity, and can be categorized from low to high risk. Development of a risk stratification tool for these patients is important f...

The Camouflage Machine: Optimizing protective coloration using deep learning with genetic algorithms.

Evolution; international journal of organic evolution
Evolutionary biologists frequently wish to measure the fitness of alternative phenotypes using behavioral experiments. However, many phenotypes are complex. One example is coloration: camouflage aims to make detection harder, while conspicuous signal...

Deep learning-Based 3D inpainting of brain MR images.

Scientific reports
The detailed anatomical information of the brain provided by 3D magnetic resonance imaging (MRI) enables various neuroscience research. However, due to the long scan time for 3D MR images, 2D images are mainly obtained in clinical environments. The p...