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Dataset results
97 results for “remote assessment”
Assessment of Compliance With Monitoring Conducted by a Physician in Person or by a Nurse in Remote Monitoring
ClinicalTrials.gov study NCT05500391. IPD Sharing: Not stated. Countries: 1. Publications: 5.
Assessment of Physiological Parameters Measurements (Heart Rate, Respiratory Rate, and Oxygen Saturation) by Standard Acquisition System Compared Remote Photoplethysmography Imaging System l
ClinicalTrials.gov study NCT04660318. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Remote Cognitive Multidomain Assessment in People With Cognitive Disorders
ClinicalTrials.gov study NCT06078332. IPD Sharing: Not stated. Countries: 1. Publications: 5.
Clinical Feasibility of Speech Phenotyping for Remote Assessment of Neurodegenerative and Psychiatric Disorders
ClinicalTrials.gov study NCT04939818. IPD Sharing: UNDECIDED. Countries: 1. Publications: 1.
Assessing the Impact of Vidéo Remote Sign Language Interpreting in Healthcare
ClinicalTrials.gov study NCT05966623. IPD Sharing: NO. Countries: 1. Publications: 2.
Remote Cognitive Assessment and Wearable Device While Assessing the Impact of Metformin in Patients With History of Cranial Radiation Therapy
ClinicalTrials.gov study NCT06377696. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Remote Cognitive Assessment for Surgical Patients
ClinicalTrials.gov study NCT05566275. IPD Sharing: NO. Countries: 1. Publications: 3.
Compare Remote Patient Management and Standard Care in CRT-D and ICD-patients to Assess the Effect on Heart Failure
ClinicalTrials.gov study NCT00730548. IPD Sharing: NO. Countries: 1. Publications: 2.
Assessment of the Prognosis of Persistent Left Bundle Branch Block (LBBB)After Transcatheter Aortic Valve Implantation (TAVI ) by an Electrophysiological and Remote Monitoring Risk-adapted Algorithm
ClinicalTrials.gov study NCT02482844. IPD Sharing: Not stated. Countries: 1. Publications: 1.
ImplementatioN of Remote Surgical wOund Assessment During the coviD-19 pandEmic
ClinicalTrials.gov study NCT05069103. IPD Sharing: YES. Countries: 1. Publications: 2.
Pilot Study Assessing the Feasibility and Impact of a Remote Adapted Physical Activity Program on Quality of Life in Patients With Inflammatory Bowel Disease (IBD)
ClinicalTrials.gov study NCT07191106. IPD Sharing: Not stated. Countries: 1. Publications: 4.
REmote Assessment and Dynamic Response Intervention
ClinicalTrials.gov study NCT04542109. IPD Sharing: YES. Countries: 1. Publications: 1.
Remotely Guided Ultrasound Among Non-Medical Personnel To Assess Normal Lung Parenchyma
ClinicalTrials.gov study NCT03469466. IPD Sharing: NO. Countries: 1. Publications: 4.
Remote Neuropsychological Assessment of Patients With Neurological Disorders and Injuries
ClinicalTrials.gov study NCT05819008. IPD Sharing: NO. Countries: 1. Publications: 21.
Remote Assessment of Lung Disease and Impact on Physical and Mental Health
ClinicalTrials.gov study NCT05630599. IPD Sharing: UNDECIDED. Countries: 1. Publications: 1.
Evaluating natural experiments in ecology: using synthetic controls in assessments of remotely-sensed land-treatments
Many important ecological phenomena occur on large spatial scales and/or are unplanned and thus do not easily fit within analytical frameworks which rely on randomization, replication, and interspersed a priori controls for statistical comparison. Analyses of such large-scale, natural experiments are common in the health and econometrics literature, where techniques have been developed to derive insight from large, noisy observational datasets. Here, we apply a technique from this literature, synthetic control, to assess landscape change with remote sensing data. The basic data requirements for synthetic control include: (1) a discrete set of treated and un-treated units, (2) a known date of treatment intervention, and (3) timeseries response data that includes both pre- and post-treatment outcomes for all units. Synthetic control generates a response metric for treated units relative to a no-action alternative based on prior relationships between treated and unexposed groups. Using simulations and a case study involving a large-scale brush clearing management event, we show how synthetic control can intuitively infer treatment effect sizes from satellite data, even in the presence of confounding noise from climate anomalies, long-term vegetation dynamics, or sensor errors. We find that accuracy depends on the number and quality of potential control units, highlighting the importance of selecting appropriate control populations. Although we consider the synthetic control approach in the context of natural experiments with remote sensing data, we expect the methodology to have wider utility in ecology, particularly for systems with large, complex, and poorly replicated experimental units.
Data from: Bioclimatic variables derived from remote sensing: assessment and application for species distribution modeling
Remote sensing techniques offer an opportunity to improve biodiversity modeling and prediction worldwide. Yet, to date, the weather-station based WorldClim dataset has been the primary source of temperature and precipitation information used in correlative species distribution models. WorldClim consists of grids interpolated from in situ station data recorded primarily from 1960 to 1990. Those datasets suffer from uneven geographic coverage, with many areas of Earth poorly represented. Here, we compare two remote sensing data sources for the purposes of biodiversity prediction: MERRA climate reanalysis data and AMSR-E, a pure remote sensing data source. We use these data to generate novel temperature-based bioclimatic information and to model the distributions of 20 species of vertebrates endemic to four regions of South America: Amazonia, the Atlantic Forest, the Cerrado, and Patagonia. We compare the bioclimatic datasets derived from MERRA and AMSR-E information with in situ station data, and contrast species distribution models based on these two products to models built with WorldClim. Surface temperature estimates provided by MERRA and AMSR-E showed warm temperature biases relative to the in situ data fields, but the reliability of these datasets varied in geographic space. Species distribution models derived from the MERRA data performed equally well (in Cerrado, Amazonia, and Patagonia) or better (Atlantic Forest) than models built with the WorldClim data. In contrast, the performance of models constructed with the AMSR-E data was similar to (Amazonia, Atlantic Forest, Cerrado) or worse than (Patagonia) that of models built with WorldClim data. Whereas this initial comparison assessed only temperature fields, efforts to estimate precipitation from remote sensing information hold great promise; furthermore, other environmental datasets with higher spatial and temporal fidelity may improve upon these results.
Assessing environmental DNA metabarcoding and camera trap surveys as complementary tools for biomonitoring of remote desert water bodies
<p>Biodiversity assessments are indispensable tools for planning and monitoring conservation strategies. Camera traps (CT) are widely used to monitor wildlife and have proven their usefulness. Environmental DNA (eDNA)-based approaches are increasingly implemented for biomonitoring, combining sensitivity, high taxonomic coverage and resolution, non-invasiveness and easiness of sampling, but remain challenging for terrestrial fauna. However, in remote desert areas where scattered water bodies attract terrestrial species, which release their DNA into the water, this method presents a unique opportunity for their detection. In order to identify the most efficient method for a given study system, comparative studies are needed. Here, we compare CT and DNA metabarcoding of water samples collected from two desert ecosystems, the Trans-Altai Gobi in Mongolia and the Kalahari in Botswana. We recorded with CT the visiting patterns of wildlife and studied the correlation with the biodiversity captured with the eDNA approach. The aim of the present study was threefold: a) to investigate how well waterborne eDNA captures signals of terrestrial fauna in remote desert environments, which have been so far neglected in terms of biomonitoring efforts; b) to compare two distinct approaches for biomonitoring in such environments and c) to draw recommendations for future eDNA-based biomonitoring. We found significant correlations between the two methodologies and describe a detectability score based on variables extracted from CT data and the visiting patterns of wildlife. This supports the use of eDNA-based biomonitoring in these ecosystems and encourages further research to integrate the methodology in the planning and monitoring of conservation strategies.</p>
Remote Assessment of OCT Scans for BCC Detection
ClinicalTrials.gov study NCT06273709. IPD Sharing: UNDECIDED. Countries: 0. Publications: 1.
Feasibility of Remote Activity Assessment and PRO Collection Among Transgender Cancer Survivors
ClinicalTrials.gov study NCT05391217. IPD Sharing: NO. Countries: 1. Publications: 0.
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Allen Brain Atlas
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DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.