AIMC Topic: Smartphone

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Machine-Learning Analysis of Voice Samples Recorded through Smartphones: The Combined Effect of Ageing and Gender.

Sensors (Basel, Switzerland) Sep 4, 2020
BACKGROUND: Experimental studies using qualitative or quantitative analysis have demonstrated that the human voice progressively worsens with ageing. These studies, however, have mostly focused on specific voice features without examining their dynam...
Machine Learning Female Aged Aged, 80 and over Humans Middle Aged Adolescent Smartphone Speech Acoustics Voice Young Adult Adult Male Aging
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Predicting Early Warning Signs of Psychotic Relapse From Passive Sensing Data: An Approach Using Encoder-Decoder Neural Networks.

JMIR mHealth and uHealth Aug 31, 2020
BACKGROUND: Schizophrenia spectrum disorders (SSDs) are chronic conditions, but the severity of symptomatic experiences and functional impairments vacillate over the course of illness. Developing unobtrusive remote monitoring systems to detect early ...
Recurrence Text Messaging Neural Networks, Computer Female Young Adult Adult Male Middle Aged Smartphone Schizophrenia Humans
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Toward automated severe pharyngitis detection with smartphone camera using deep learning networks.

Computers in biology and medicine Aug 20, 2020
PURPOSE: Severe pharyngitis is frequently associated with inflammations caused by streptococcal pharyngitis, which can cause immune-mediated and post-infectious complications. The recent global pandemic of coronavirus disease (COVID-19) encourages th...
Image Interpretation, Computer-Assisted Photography Pneumonia, Viral Coronavirus Infections COVID-19 Pharyngitis Deep Learning Pharynx Humans Smartphone Telemedicine Pandemics
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Big data in epilepsy: Clinical and research considerations. Report from the Epilepsy Big Data Task Force of the International League Against Epilepsy.

Epilepsia Aug 7, 2020
Epilepsy is a heterogeneous condition with disparate etiologies and phenotypic and genotypic characteristics. Clinical and research aspects are accordingly varied, ranging from epidemiological to molecular, spanning clinical trials and outcomes, gene...
Humans Brain Electronic Health Records Societies, Medical Common Data Elements Research Support as Topic Telemedicine Information Dissemination Advisory Committees Biological Ontologies Neuroimaging Computer Security Stakeholder Participation Electrocorticography Biomedical Research Smartphone Deep Learning Genomics Big Data Epilepsy Wearable Electronic Devices Confidentiality
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Using machine learning for real-time BAC estimation from a new-generation transdermal biosensor in the laboratory.

Drug and alcohol dependence Aug 1, 2020
BACKGROUND: Transdermal biosensors offer a noninvasive, low-cost technology for the assessment of alcohol consumption with broad potential applications in addiction science. Older-generation transdermal devices feature bulky designs and sparse sampli...
Female Adult Male Smartphone Humans Machine Learning Alcohol Drinking Breath Tests Biosensing Techniques Family Characteristics Ethanol Laboratories
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goFOOD: An Artificial Intelligence System for Dietary Assessment.

Sensors (Basel, Switzerland) Jul 31, 2020
Accurate estimation of nutritional information may lead to healthier diets and better clinical outcomes. We propose a dietary assessment system based on artificial intelligence (AI), named goFOOD. The system can estimate the calorie and macronutrient...
Nutrition Assessment Energy Intake Smartphone Meals Artificial Intelligence
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Screening of Parkinsonian subtle fine-motor impairment from touchscreen typing via deep learning.

Scientific reports Jul 28, 2020
Fine-motor impairment (FMI) is progressively expressed in early Parkinson's Disease (PD) patients and is now known to be evident in the immediate prodromal stage of the condition. The clinical techniques for detecting FMI may not be robust enough and...
Humans Female Mass Screening Male Self Report Parkinson Disease Middle Aged Deep Learning Confidence Intervals Cohort Studies Motor Activity ROC Curve Smartphone
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Parkinson's disease detection from 20-step walking tests using inertial sensors of a smartphone: Machine learning approach based on an observational case-control study.

PloS one Jul 23, 2020
Parkinson's disease (PD) is a neurodegenerative disease inducing dystrophy of the motor system. Automatic movement analysis systems have potential in improving patient care by enabling personalized and more accurate adjust of treatment. These systems...
Smartphone Support Vector Machine Parkinson Disease Signal Processing, Computer-Assisted Exercise Test Male Walking Middle Aged Statistics as Topic Humans Case-Control Studies Machine Learning Cohort Studies Female Aged
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Artificial intelligence mobile health platform for early detection of COVID-19 in quarantine subjects using a wearable biosensor: protocol for a randomised controlled trial.

BMJ open Jul 22, 2020
INTRODUCTION: There is an outbreak of COVID-19 worldwide. As there is no effective therapy or vaccine yet, rigorous implementation of traditional public health measures such as isolation and quarantine remains the most effective tool to control the o...
Randomized Controlled Trials as Topic Quarantine Coronavirus Infections Telemedicine COVID-19 Testing Heart Rate Early Diagnosis Hong Kong SARS-CoV-2 Wearable Electronic Devices Betacoronavirus Skin Temperature Humans Smartphone Pneumonia, Viral Cloud Computing Artificial Intelligence Mobile Applications Blood Gas Monitoring, Transcutaneous Respiratory Rate Pandemics Clinical Laboratory Techniques COVID-19
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Opportunities and challenges in the collection and analysis of digital phenotyping data.

Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology Jul 17, 2020
The broad adoption and use of smartphones has led to fundamentally new opportunities for capturing social, behavioral, and cognitive phenotypes in free-living settings, outside of research laboratories and clinics. Predicated on the use of existing p...
Research Design Phenotype Smartphone Data Collection Machine Learning
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