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100 results for “Medical Dataset”
Data from: Transforming medical education in Liberia through an international community of inquiry (2018 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>
PolyMed: A Medical Dataset Addressing Disease Imbalance for Robust Automatic Diagnosis Systems
<p>We introduce the PolyMed dataset, designed to address the limitations of existing medical case data for Automatic Diagnosis Systems (ADS). ADS assists doctors by predicting diseases based on patients' basic information, such as age, gender, and symptoms. However, these systems face challenges due to imbalanced disease label data and difficulties in accessing or collecting medical data. To tackle these issues, the PolyMed dataset has been developed to improve the evaluation of ADS by incorporating medical knowledge graph data and diagnosis case data. The dataset aims to provide comprehensive evaluation, include diverse disease information, effectively utilize external knowledge, and perform tasks closer to real-world scenarios.</p> <p>We have also made the data collection tools publicly available to enable researchers and other interested parties to contribute additional data in a standardized format. These tools feature a range of customizable input fields that can be selectively utilized according to the user's specific requirements, ensuring consistency and professionalism in the data collection process.</p> <p>All train and test code of our data available in https://github.com/krchanyang/PolyMed</p>
COVID-19 medical image datasets
<p>This repository contains three curated datasets for the medical image classification described in the paper entitled "Explainable deep transfer learning fine-tunning with domain adaptation enables trustworthy COVID-19 prediction".</p>
Dataset for the paper "Exposure of medical students to sexism and sexual harassment and their association with mental health: a cross-sectional study at a Swiss medical school" published in BMJ Open (2023)
<p><strong>Full reference of the paper: </strong></p> <p>Barbier JM, Carrard V, Schwarz J, et al. Exposure of medical students to sexism and sexual harassment and their association with mental health: a cross-sectional study at a Swiss medical school. BMJ Open 2023;13:e069001. doi:10.1136/bmjopen-2022-069001</p>
Antimicrobial Resistance Microbiological Dataset (ARMD-UTSW): A deidentified collection of electronic health records, from a quaternary, academic medical center, for antimicrobial resistance research
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Data from: Transforming medical education in Liberia through an international community of inquiry (2016 dataset)
Open the record for dataset details and reuse information.
Data from: Transforming medical education in Liberia through an international community of inquiry (2017 dataset)
Open the record for dataset details and reuse information.
Data from: Transforming medical education in Liberia through an international community of inquiry (2018 dataset)
Open the record for dataset details and reuse information.
datasets bmc medical education1
<p>Datasets of a research developed at Federal University of Viçosa, Brazil; it contains data from a survey on health-related quality of life, developed among medical students, at Federal University of Viçosa.</p>
datasets bmc medical education
<p>Datasets of a research developed at Federal University of Viçosa, Brazil; it contains data from a survey on health-related quality of life, developed among medical students, at Federal University of Viçosa.</p> <p> </p>
Dataset: Survey on the actual situation of antibiotic resistant bacteria detection by nucleic acid amplification test in clinical microbiology laboratories at hospitals in Japan: Online survey of participants in workshops organized by the Nara Association of Medical Technologists
<p>The coronavirus disease 2019 pandemic has led to the widespread use of the nucleic acid amplification test (NAAT), along with an increase in demand for SARS-CoV-2 tests. NAAT has been used to detect antimicrobial resistance (AMR) genes since before the pandemic, but the test has been performed in a limited number of facilities. We investigated the current status and background of Japanese clinical laboratories by surveying the implementation of genotypic AST in NAAT, which has become widespread owing to the pandemic. This means that 59% of the respondents possessed NAAT and were using it for genotypic AST. GeneXpert and FilmArray were introduced in the majority of cases (62.5% and 82.6%, respectively), with the pandemic as the trigger. More than half of the respondents cited “rapid detection” (56.0%) and “ICT requests” (52.4%) as the reasons for introducing the system. Regarding usefulness, “contribution to infectious disease treatment” (74.1%) showed the highest percentage. Among the respondents who cited “not implemented”, the most frequent responses were “I have no plans, but I want to do it.” (38.1%) and “would do so if requested by a physician” (33.3%). The most common reason for not implementing the system was concern about increased workload (52.9%). We believe that this is due to changes in the working environment caused by the pandemic and the characteristics of Japanese society. In the future, to promote the adoption of genotypic AST, it will be necessary to approach it through reports on its usefulness from domestic facilities, and simultaneously, improving and enhancing efficiency in work processes will also be essential.</p>
Quality and Utility of European Cardiovascular and Orthopaedic Registries for the Regulatory Evaluation of Medical Device Safety and Performance Across the Implant Lifecycle: A Systematic Review - Dataset
<p><strong>Background: </strong>The European Union Medical Device Regulation (MDR) requires manufacturers to undertake post-market clinical follow-up (PMCF) to assess the safety and performance of their devices following approval and Conformité Européenne (CE) marking. The quality and reliability of device registries for this Regulation have not been reported. As part of the Coordinating Research and Evidence for Medical Devices (CORE-MD) project, we identified and reviewed European cardiovascular and orthopaedic registries to assess their structures, methods, and suitability as data sources for regulatory purposes.</p> <p><strong>Methods: </strong>Regional, national and multi-country European cardiovascular (coronary stents and valve repair/replacement) and orthopaedic (hip/knee prostheses) registries were identified using a systematic literature search. Annual reports, peer-reviewed publications, and websites were reviewed to extract publicly available information for 33 items related to structure and methodology in six domains and also for reported outcomes.</p> <p><strong>Results: </strong>Of the 20 cardiovascular and 26 orthopaedic registries fulfilling eligibility criteria, a median of 33% (IQR: 14%-71%) items for cardiovascular and 60% (IQR: 28%-100%) items for orthopaedic registries were reported, with large variation across domains. For instance, no cardiovascular and 16 (62%) orthopaedic registries reported patient/ procedure-level completeness. No cardiovascular and 5 (19%) orthopaedic registries reported outlier performances of devices, but each with a different outlier definition. There was large heterogeneity in reporting on items, outcomes, definitions of outcomes, and follow-up durations.</p> <p><strong>Conclusion: </strong>European cardiovascular and orthopaedic device registries could improve their potential as data sources for regulatory purposes by reaching consensus on standardised reporting of structural and methodological characteristics to judge the quality of the evidence as well as outcomes.</p>
Dataset for "Definition and rationale for placebo composition: Cross-sectional analysis of randomized trials and protocols published in high-impact medical journals"
<p>Contains our data extraction sheets</p>
Dataset for a publication: "Silver-enriched Microdomain Patterns as Advanced Bactericidal Coatings for Polymer-based Medical Devices"
<p>The data set contains the data that were used within the article "Silver-enriched Microdomain Patterns as Advanced Bactericidal Coatings for Polymer-based Medical Devices".</p> <p> </p> <p> </p>
Dataset for Spence et al., "Availability of study protocols for randomized trials published in high-impact medical journals: cross-sectional analysis" (CITATION)
<p>Contains our extraction sheets (as SAS data files), code to calculate the values in the tables in our manuscript, and a supplemental file with additional notes on methods used in our study.</p>
Large Scale Medical Image Dataset
<p>Multiple dataset from different sources has been aggregated to create a large-scale medical image benchmark dataset in order to measure its performance. As each of the dataset’s images are of different sizes, the images are resized to 3 × 224 × 224 before the training process. This dataset contains total of 35 diseases of 4 different modality and is divided into train, validation, and test with a ratio of 7 : 1 : 2.</p>
pGAN Synthetic Dataset: A Deep Learning Approach to Private Data Sharing of Medical Images Using Conditional GANs
<p>Synthetic dataset for <strong>A Deep Learning Approach to Private Data Sharing of Medical Images Using Conditional GANs</strong></p> <p><strong> Dataset specification:</strong></p> <ul> <li>MRI images of Vertebral Units labelled based on region</li> <li>Dataset is comprised of 10000 pairs of images and labels</li> <li>Image and label pair number k can be selected by: synthetic_dataset['images'][k] and synthetic_dataset['regions'][k]</li> <li>Images are 3D of size (9, 64, 64)</li> <li>Regions are stored as an integer. Mapping is 0: cervical, 1: thoracic, 2: lumbar</li> </ul> <p>Arxiv paper: <a href="https://arxiv.org/abs/2106.13199">https://arxiv.org/abs/2106.13199</a><br> Github code: <a href="https://github.com/tcoroller/pGAN/">https://github.com/tcoroller/pGAN/</a></p> <p>Abstract:</p> <p>Sharing data from clinical studies can facilitate innovative data-driven research and ultimately lead to better public health. However, sharing biomedical data can put sensitive personal information at risk. This is usually solved by anonymization, which is a slow and expensive process. An alternative to anonymization is sharing a synthetic dataset that bears a behaviour similar to the real data but preserves privacy. As part of the collaboration between Novartis and the Oxford Big Data Institute, we generate a synthetic dataset based on COSENTYX Ankylosing Spondylitis (AS) clinical study. We apply an Auxiliary Classifier GAN (ac-GAN) to generate synthetic magnetic resonance images (MRIs) of vertebral units (VUs). The images are conditioned on the VU location (cervical, thoracic and lumbar). In this paper, we present a method for generating a synthetic dataset and conduct an in-depth analysis on its properties of along three key metrics: image fidelity, sample diversity and dataset privacy.</p>
Risky Play: A Risk-based Case Study for Common Mode Current Assessment of a Medical Plasma Device (Dataset)
<p>This dataset contains raw- and de-embedding data which are the source of the referenced publication's plots.</p> <p>Uploaded are raw common mode current measurements in dBm as a .mat file, touchstone files for the cable used and characteristics of the Fischer Customs Communication F-75 and F-2000 probes as .csv, both used for de-embedding cable and current probe from the raw data. </p> <p>In addition, touchstone files of the input impedance measurements are contained.</p> <p>This research is part of a project that has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 955816 (MSCA-ETN ETERNITY)</p>
Ambiguity in medical concept normalization: An analysis of types and coverage in electronic health record datasets
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Critical Gaps in Medical Research Reporting by Online News Media: Dataset
<p>Dataset for <strong>Critical Gaps in Medical Research Reporting by Online News Media</strong></p>
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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.