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100
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Dataset results
100 results for “Medical Dataset”
Dataset: enVVeno Medical Corporation (NVNO) Stock Performance
This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.
Dataset: NeuroOne Medical Technologies Corporation (NMTC) Stock Performance
This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.
Dataset: Inari Medical, Inc. (NARI) Stock Performance
This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.
Dataset: Modular Medical, Inc. (MODD) Stock Performance
This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.
Dataset: Merit Medical Systems, Inc. (MMSI) Stock Performance
This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.
Dataset: Horizon Kinetics Medical ETF (MEDX) Stock Performance
This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.
Dataset: Meihua International Medical Technologies Co., Ltd. (MHUA) Stock Performance
This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.
Dataset: Microbot Medical Inc. (MBOT) Stock Performance
This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.
Dataset: KORU Medical Systems, Inc. (KRMD) Stock Performance
This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.
Dataset: ICU Medical, Inc. (ICUI) Stock Performance
This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.
Dataset: SeaStar Medical Holding Corporation (ICUCW) Stock Performance
This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.
Dataset: SeaStar Medical Holding Corporation (ICU) Stock Performance
This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.
Dataset: IceCure Medical Ltd (ICCM) Stock Performance
This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.
Dataset: Helius Medical Technologies, Inc. (HSDT) Stock Performance
This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.
Dataset for Medical Image Processing in Python Carpentries lesson
<p>This dataset contains a collection of medical imaging files for use in the <a href="https://github.com/esciencecenter-digital-skills/medical-image-processing">"Medical Image Processing with Python" lesson</a>, originally developed by the <a href="https://www.esciencecenter.nl/">Netherlands eScience Center</a>. </p> <p>The dataset includes:</p> <ol> <li>SimpleITK compatible files: MRI T1 and CT scans (<em>training_001_mr_T1.mha, training_001_ct.mha</em>), digital X-ray (<em>digital_xray.dcm</em> in DICOM format), neuroimaging data (<em>A1_grayT1.nrrd, A1_grayT2.nrrd</em>). Data have been downloaded from <a href="https://insightsoftwareconsortium.github.io/SimpleITK-Notebooks/Python_html/00_Setup.html">here</a>. </li> <li>MRI data: a T2-weighted image (<em>OBJECT_phantom_T2W_TSE_Cor_14_1.nii</em> in NIfTI-1 format). Data have been downloaded from <a href="https://zenodo.org/records/6467772">here</a>. </li> <li>Example images for the machine learning lesson: chest X-rays (<em>rotatechest.png, other_op.png</em>), cardiomegaly example (<em>cardiomegaly_cc0.png</em>).</li> <li>Array data: Array data for the Intro to Medical Imaging lesson. Numpy arrays were created by processing and manipulation of publicly available data i.e. from <a href="https://doi.org/10.1109/TNS.1974.6499235">the Schepp Logan phantom</a> and from the <a href="https://fastmri.med.nyu.edu/">NYU FastMRI dataset</a> <div> </div> </li> <li>Additional data: to be added</li> </ol> <p>These files represent various medical imaging modalities and formats commonly used in clinical research and practice. They are intended for educational purposes, allowing students to practice image processing techniques, machine learning applications, and statistical analysis of medical images using Python libraries such as scikit-image, pydicom, and SimpleITK.</p>
Datasets for "A Bibliometric Study of Medical Tourism" paper
<p>This datasets is used during the "<strong>A Bibliometric Study of Medical Tourism</strong>" study. The data were collected from the SCOPUS database. A title search on SCOPUS based on the search term retrieved 1,535 documents consisting of 969 Articles, 197 book chapters, 102 review papers, 83 conference papers, while the rest were notes, letter, editorials, short surveys, books, and erratum. . The timespan covered ranged from 1<sup>st</sup> of 1952 to 2020.</p>
Dataset for the paper "The relationship between medical students' empathy, mental health, and burnout: A cross-sectional study" published in Medical Teacher (2022)
<p><strong>Full reference of the paper: </strong></p> <p>Valerie Carrard, Céline Bourquin, Sylvie Berney, Katja Schlegel, Jacques Gaume, Pierre-Alexandre Bart, Martin Preisig, Marianne Schmid Mast & Alexandre Berney (2022): The relationship between medical students’ empathy, mental health, and burnout: A cross-sectional study, Medical Teacher, DOI: <a href="https://doi.org/10.1080/0142159X.2022.2098708">10.1080/0142159X.2022.2098708</a></p>
Medical-Waste-4.0-Dataset: v0.1
<p>This dataset was acquired in the framework of the Medical Waste Treating 4.0 funded by the Tuscany Region.</p> <p>The dataset aims to be a valuable resource for devising and testing computer vision methods for the primary sorting of medical waste.</p> <p>Acquisition device: OAK-D camera with tech specs available here https://docs.luxonis.com/projects/hardware/en/latest/pages/BW1098OAK.html</p> <p>Each sample consists of three images, namely an RGB image and a stereo pair:</p> <p>RGB: 1920 x 1080<br> Grayscale: 640 x 400 </p> <p>Example:<br> timestamp.jpg = RGB Image<br> timestamp_r.png = Right image in the stereo pair<br> timestamp_l.png = Left image in the stereo pair</p> <p><br> Categories:<br> - gauze<br> - glove pair latex<br> - glove pair nitrile<br> - glove pair surgery<br> - glove single latex<br> - glove single nitrile<br> - glove single surgery<br> - medical cap<br> - medical glasses<br> - shoe cover pair<br> - shoe cover single<br> - test tube<br> - urine bag</p>
Data from: Transforming medical education in Liberia through an international community of inquiry (2017 dataset)
<p>A critical component of building capacity in Liberia's physician workforce involves strengthening the country's only medical school, A.M. Dogliotti College of Medicine. Beginning in 2015, senior health sector stakeholders in Liberia invited faculty and staff from U.S. academic institutions and non-governmental organizations to join a partnership focused on improving undergraduate medical education in Liberia. Over the subsequent six years, the members of this partnership came together through an iterative, mutual-learning process and created what William Torbert et al describe as a "community of inquiry," in which practitioners and researchers pair action and inquiry toward evidence-informed practice and organizational transformation. This community of inquiry developed around a few key institutional and interpersonal relationships but expanded over time. Incorporating faculty, practitioners, and students from Liberia and the U.S., the community of inquiry consistently focused on following the vision, goals, and priorities of leadership in Liberia, irrespective of funding source or institutional affiliation. The work of the community of inquiry has incorporated multiple mixed methods assessments, stakeholder discussions, strategic planning, and collaborative self-reflection, resulting in transformation of M.D. education in Liberia. We suggest that the community of inquiry approach reported here can serve as a model for others seeking to form sustainable, international global health partnerships focused on organizational transformation.</p>
Data from: Transforming medical education in Liberia through an international community of inquiry (2016 dataset)
<p class="MsoNormal">A critical component of building capacity in Liberia's physician workforce involves strengthening the country's only medical school, A.M. Dogliotti College of Medicine. Beginning in 2015, senior health sector stakeholders in Liberia invited faculty and staff from U.S. academic institutions and non-governmental organizations to join a partnership focused on improving undergraduate medical education in Liberia. Over the subsequent six years, the members of this partnership came together through an iterative, mutual-learning process and created what William Torbert et al describe as a "community of inquiry," in which practitioners and researchers pair action and inquiry toward evidence-informed practice and organizational transformation. This community of inquiry developed around a few key institutional and interpersonal relationships but expanded over time. Incorporating faculty, practitioners, and students from Liberia and the U.S., the community of inquiry consistently focused on following the vision, goals, and priorities of leadership in Liberia, irrespective of funding source or institutional affiliation. The work of the community of inquiry has incorporated multiple mixed methods assessments, stakeholder discussions, strategic planning, and collaborative self-reflection, resulting in transformation of M.D. education in Liberia. We suggest that the community of inquiry approach reported here can serve as a model for others seeking to form sustainable, international global health partnerships focused on organizational transformation.</p>
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.