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Dataset results
1,943 results for “machine learning”
Introduction to machine learning
<p>Recording of the presentation given at the Summer School</p>
Costs and Benefits of Machine Learning Software Defect Prediction
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MACHINE LEARNING APPLICATIONS IN AGRICULTURE
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Efficient multiscale-model construction using machine learning: introducing the CarveAdornCurate cloud-based platform
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Machine Learning Approaches for Characterizing the Raindrop Size Distributions in Western Pacific Tropical Cyclones
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Database and Images of Cutaneous Leishmaniasis Direct Smears: Detection of Leishmania spp. Parasite in Microscopy Images Using Machine Learning Algorithms.
<p>This database and images were created for Cutaneous Leishmaniasis research, mainly for computer vision and machine learning studies. The dataset is organized into two main folders, designed to facilitate access and analysis of the images and corresponding labeling data.</p> <p>The first folder, 'EPVIEW_LC_S,' contains a total of 500 PNG images, each with a resolution of 2592 x 1944 pixels. These images represent positive direct smears with Cutaneous Leishmaniasis. The organization of the images follows a hierarchical structure, distributed across 50 folders (L1 – L50), where each folder symbolizes an individual exam slide. Inside each main folder, there are two subfolders that house the images of the two samples present on each slide, with 5 images per subfolder, corresponding to the 5 microscopic fields captured for each sample. This results in a set of 10 images per slide.</p> <p>The second folder, 'Etiquetado_LC_T,' contains the labeling process carried out for each image with the collaboration of two experts in the field. A total of 7,905 <em>Leishmania spp.</em> parasites were identified and labeled. Using bounding boxes, the precise dimensions of the parasites were recorded, including width, height, and the central location of each parasite within the image, with (x, y) coordinates, along with the parasite label. This information was stored in JSON files, whose names correspond directly to the images they reference, ensuring an accurate relationship that facilitates the use of the data for research purposes. The organization structure of the labeling folder mirrors that of the image folder.</p>
A Dataset and Machine Learning Approach to Classify and Augment Interface Elements of Household Appliances to Support People with Visual Impairment
<p>Here, we provide a dataset of images of interfaces from household appliances, where all interface elements are labled with one of five different types of interface elements. Further, we provide auxillary materials to use and extend the dataset.</p>
Analysis data for "Reference Architecture for Serverless Machine Learning"
<p>Data used for analysis in my bachelor thesis.</p>
The role of continental alkaline magmatism in mantle carbon outflux constrained by a machine learning analysis of zircon
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A Clinical Trial to Evaluate the Efficacy of the Morley Medical Sepsis (MMS) Software Device in Predicting Sepsis in Adult Patients Using Artificial Intelligence (AI) Machine Learning Algorithms
ClinicalTrials.gov study NCT04606862. IPD Sharing: Not stated. Countries: 0. Publications: 0.
MUSCLE-ML: Multimodal Integration of Muscle Strength, Structure by Machine Learning for Precision Rehabilitation After ACL Injury
ClinicalTrials.gov study NCT07284771. IPD Sharing: Not stated. Countries: 0. Publications: 0.
External, Multicentre Validation of a Machine-Learning Model to Predict Colonic Adenoma in Indian Adults
ClinicalTrials.gov study NCT07329816. IPD Sharing: NO. Countries: 0. Publications: 0.
Machine Learning for Predicting and Managing Quality of Life in Lung Cancer Immunotherapy Patients
ClinicalTrials.gov study NCT06725225. IPD Sharing: NO. Countries: 0. Publications: 0.
Predicting Outcomes From tDCS Intervention in Parkinson' Disease Using Electroencephalographic Biomarkers and Machine Learning Approach: the PREDICT Study Protocol
ClinicalTrials.gov study NCT04819061. IPD Sharing: Not stated. Countries: 0. Publications: 0.
Machine Learning-Based Risk Stratification for Fistula Formation After Perianal Abscess Drainage
ClinicalTrials.gov study NCT07019532. IPD Sharing: YES. Countries: 0. Publications: 0.
Machine Learning Model Guided by TLS Predicts Survival and Immune Features in Gastric Cancer
ClinicalTrials.gov study NCT06979817. IPD Sharing: Not stated. Countries: 0. Publications: 0.
Sex-Specific Machine Learning Models to Predict Distant Metastasis in Liver Cancer
ClinicalTrials.gov study NCT07386639. IPD Sharing: NO. Countries: 0. Publications: 0.
Application of an Antimicrobial Stewardship Program in Brazilian ICUs Using Machine Learning Techniques and an Educational Model
ClinicalTrials.gov study NCT05312034. IPD Sharing: Not stated. Countries: 0. Publications: 0.
Machine Learning and Artificial Intelligence Algorithms to Optimize the Performance and Delivery of Acute Dialysis
ClinicalTrials.gov study NCT07312929. IPD Sharing: UNDECIDED. Countries: 0. Publications: 0.
Telemedicine Notifications With Machine Learning for Postoperative Care
ClinicalTrials.gov study NCT03974828. IPD Sharing: NO. Countries: 0. Publications: 0.
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.