Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
54
datasets available to search
ShareScore release 0.9.0
Dataset results
54 results for “algorithmic system”
Could the Advanced Hybrid Closed-Loop System Algorithm Provide Postprandial Normoglycemia After a High-Fat, High-Protein Meal
ClinicalTrials.gov study NCT06848933. IPD Sharing: UNDECIDED. Countries: 1. Publications: 0.
Development of an Aid to Melanoma Detection Using Artificial Intelligence Algorithms Based on Images From the VECTRA 3D System.
ClinicalTrials.gov study NCT06999499. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Validation of CardioMEMS HF System Cardiac Output Algorithm IDE
ClinicalTrials.gov study NCT05428384. IPD Sharing: NO. Countries: 1. Publications: 0.
Fever Algorithm Development of a Non-invasive Wearable Core Body Temperature Sensor System in Intensive Care Unit Patients
ClinicalTrials.gov study NCT04182945. IPD Sharing: UNDECIDED. Countries: 1. Publications: 0.
Clinical Investigation of a Modified Staged Treatment Algorithm Using the AeriSeal System
ClinicalTrials.gov study NCT02877459. IPD Sharing: NO. Countries: 3. Publications: 0.
Algorithms for Programming DBS Systems for ET
ClinicalTrials.gov study NCT03984643. IPD Sharing: NO. Countries: 1. Publications: 0.
A Prototype AI Algorithm Versus Liver Imaging Reporting and Data System (LI-RADS) Criteria in Diagnosing HCC on CT
ClinicalTrials.gov study NCT06626087. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Use of the VasoNova VPS System During PICC Placement in an Algorithm Confirmation Study Using Fluoroscopy
ClinicalTrials.gov study NCT01232933. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Care Algorithm and Clinic Decision System on Hepatic Rehabilitation in Patients With Liver Cirrhosis
ClinicalTrials.gov study NCT06995196. IPD Sharing: YES. Countries: 1. Publications: 0.
Testing the Effects of an Algorithm for Neuropathic Pain on Patient and System Outcomes
ClinicalTrials.gov study NCT00130130. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Federal Learning Algorithm for an Intelligent Insulin Decision System for Dynamic Glucose Control in Type 2 Diabetic Patients
ClinicalTrials.gov study NCT06434623. IPD Sharing: UNDECIDED. Countries: 0. Publications: 0.
ADAPTIVE FAULT DETECTION ON LIQUID PROPULSION SYSTEMS WITH VIRTUAL SENSORS: ALGORITHMS AND ARCHITECTURES
Prior to the launch of STS-119 NASA had completed a study of an issue in the flow control valve (FCV) in the Main Propulsion System of the Space Shuttle using an adaptive learning method known as Virtual Sensors. Virtual Sensors are a class of algorithms that estimate the value of a time series given other potentially nonlinearly correlated sensor readings. In the case presented here, the Virtual Sensors algorithm is based on an ensemble learning approach and takes sensor readings and control signals as input to estimate the pressure in a subsystem of the Main Propulsion System. Our results indicate that this method can detect faults in the FCV at the time when they occur. We use the standard deviation of the predictions of the ensemble as a measure of uncertainty in the estimate. This uncertainty estimate was crucial to understanding the nature and magnitude of transient characteristics during startup of the engine. This paper overviews the Virtual Sensors algorithm and discusses results on a comprehensive set of Shuttle missions and also discusses the architecture necessary for deploying such algorithms in a real-time, closed-loop system or a human-in-the-loop monitoring system. These results were presented at a Flight Readiness Review of the Space Shuttle in early 2009.
A Generic Local Algorithm for Mining Data Streams in Large Distributed Systems
In a large network of computers or wireless sensors, each of the components (henceforth, peers) has some data about the global state of the system. Much of the system's functionality such as message routing, information retrieval and load sharing relies on modeling the global state. We refer to the outcome of the function (e.g., the load experienced by each peer) as the emph{model} of the system. Since the state of the system is constantly changing, it is necessary to keep the models up-to-date. Computing global data mining models e.g. decision trees, k-means clustering in large distributed systems may be very costly due to the scale of the system and due to communication cost, which may be high. The cost further increases in a dynamic scenario when the data changes rapidly. In this paper we describe a two step approach for dealing with these costs. First, we describe a highly efficient emph{local} algorithm which can be used to monitor a wide class of data mining models. Then, we use this algorithm as a feedback loop for the monitoring of complex functions of the data such as its k-means clustering. The theoretical claims are corroborated with a thorough experimental analysis.
Impact of Input Uncertainty on Failure Prognostic Algorithms: Extending the Remaining Useful Life of Nonlinear Systems
This paper presents a novel set of uncertainty measures to quantify the impact of input uncertainty on nonlinear prognosis systems. A Particle Filtering-based method is also presented that uses this set of uncertainty measures to quantify, in real time, the impact of load, environmen- tal, and other stresses for long-term prediction. Further- more, this work shows how these measures can be used to implement a novel feedback correction loop aimed to suggest modifications, at a system input level, with the purpose of extending the remaining useful life of a faulty nonlinear, non-Gaussian system. The correction scheme is tested and illustrated using real vibration feature data from a fatigue-driven fault in a critical aircraft compo- nent.
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
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.