cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.yuvw5y
title: Occurrence Download

description: A dataset containing 119 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-93.60892 69.5279,-93.47556 69.49173,-93.47556 69.56529,-93.51055 69.57386,-93.56808 69.58178,-93.60892 69.5279))",
 "PublishingOrg is one of (e2e717bf-551a-4917-bdc9-4fa0f342c530, 4cd08c7c-fd56-48d0-ab05-aac38aa4457e, 28eb1a3f-1c15-4a95-931a-4af90ecb574d)",
 "Year 2000-2024"
 ]
}

 The dataset includes 119 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0024622-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6073/pasta/8ce9511aa01a958ec2ba63f6d52bb98b
title: Air temperature and relative humidity data for B1 HOBO logger, 2012 - ongoing.

description: Climatological data were collected from a ridgetop climate station
 east of Niwot Ridge (B1 at 2591 m) throughout the year using a HOBO
 Pro V2 data logger mounted in a Stevenson screen. Parameters
 measured were air temperature and relative humidity
DOI: 10.71718/wryp-7h77
title: RadFusion: Multimodal Pulmonary Embolism Dataset

description: We collected data from 1794 patients susceptible to pulmonary embolism at the Stanford University Medical Center. The dataset consists of Chest CT, patient demographics and medical history. Publication link:
DOI: 10.71718/cwh3-0p32
title: MURA: MSK X-rays

description: MURA (musculoskeletal radiographs) is a large dataset of bone X-rays. Algorithms are tasked with determining whether an X-ray study is normal or abnormal.Musculoskeletal conditions affect more than 1.7 billion people worldwide, and are the most common cause of severe, long-term pain and disability, with 30 million emergency department visits annually and increasing. We hope that our dataset can lead to significant advances in medical imaging technologies which can diagnose at the level of experts, towards improving healthcare access in parts of the world where access to skilled radiologists is limited.MURA is one of the largest public radiographic image datasets. We're making this dataset available to the community and hosting a competition to see if your models can perform as well as radiologists on the task.
DOI: 10.71718/rcbp-8c35
title: MRNet: Knee MRIs

description: The MRNet dataset consists of 1,370 knee MRI exams performed at Stanford University Medical Center. The dataset contains 1,104 (80.6%) abnormal exams, with 319 (23.3%) ACL tears and 508 (37.1%) meniscal tears; labels were obtained through manual extraction from clinical reports.
DOI: 10.15468/dl.ytcvru
title: Occurrence Download

description: A dataset containing 23 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Fomitopsis officinalis (Vill.) Bondartsev & Singer",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Continent is Europe",
 "CoordinateUncertaintyInMeters is 0,1000",
 "OccurrenceStatus is Present",
 "EventDate is 1960,2024"
 ]
}

 The dataset includes 23 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0024623-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14194466
title: SC24 Repro Artifacts A2
DOI: 10.5281/zenodo.14194467
title: SC24 Repro Artifacts A2
DOI: 10.5281/zenodo.14194520
title: SC24 Repro Artifacts A2
DOI: 10.6073/pasta/2ea2ff4247d955c121f0a4cfef0556c4
title: Air temperature and relative humidity data for A1 HOBO logger, 2013 - ongoing.

description: Climatological data were collected from a ridgetop climate station
 east of Niwot Ridge (A1 at 2195 m) throughout the year using a HOBO
 Pro V2 data logger mounted in a Stevenson screen. Parameters
 measured were air temperature and relative humidity.
DOI: 10.71718/aqrb-et67
title: LERA: Lower Extremity Radiographs

description: Musculoskeletal disorders (MSDs), which encompass a wide variety of bone, soft tissue, and joint abnormalities, are a major healthcare challenge around the world. MSDs are typically diagnosed using radiographs; however, variations in diagnostic interpretation quality can often lead to diagnostic errors. This problem is often compounded by a lack of available tools to triage large volumes of unread examinations, which can result in numerous adverse downstream effects related to delay of diagnosis and treatment.The recent revolution in deep learning techniques for image analysis suggests that convolutional neural networks (CNNs) can serve as an effective tool for computer-aided detection of radiograph abnormalities. To aid computational models in accurately identifying diverse abnormalities in highly-variable radiographs of multiple body parts, we are releasing LERA (Lower Extremity RAdiographs). This dataset was used as the held-out test set in our recent study, which found that a single pre-trained CNN was effective in performing generalized abnormality detection in lower extremities [citation after publication].
DOI: 10.5285/25a03b10-52b6-7909-e063-7086abc06ce0
title: Measurements of fast fCO2 and Gas Transfer Efficiency (GTE) during the Atlantic Meridional Transect cruise AMT29 (DY110) between the 13th October 2019 and the 23rd November 2019.

description: This dataset includes CO2 fugacity (fCO2w) in underway surface seawater and Gas Transfer Efficiency (GTE) during trans-Atlantic, Atlantic Meridional Transect cruise AMT29 (DY110) from Southampton, UK to Punta Arenas, Chile between the 13th October 2019 and the 23rd November 2019. Measurements of fast underway fCO2 and gas transfer efficiency were made onboard with two segmented flow coil equilibration (SFCE) systems. Measurements were made by scientists from Plymouth Marine Laboratory and were funded by the UK Natural Environment Research Council’s ORCHESTRA project (Grant No. NE/N018095/1) and European Space Agency (ESA AMT4OceanSatFlux project, Grant No. 4000125730/18/NL/FF/gp).
DOI: 10.71718/tme3-kj32
title: INSPECT: A Multimodal Dataset for Pulmonary Embolism Diagnosis and Prognosis

description: Synthesizing information from various data sources plays a crucial role in the practice of modern medicine. Current applications of artificial intelligence in medicine often focus on single-modality data due to a lack of publicly available, multimodal medical datasets. To address this limitation, we introduce INSPECT, which contains de-identified longitudinal records from a large cohort of pulmonary embolism (PE) patients, along with ground truth labels for multiple outcomes. INSPECT contains data from 19,438 patients, including CT images, sections of radiology reports, and structured electronic health record (EHR) data (including demographics, diagnoses, procedures, and vitals). Using our provided dataset, we develop and release a benchmark for evaluating several baseline modeling approaches on a variety of important PE related tasks. We evaluate image-only, EHR-only, and fused models. Trained models and the de-identified dataset are made available for non-commercial use under a data use agreement. To the best our knowledge, INSPECT is the largest multimodal dataset for enabling reproducible research on strategies for integrating 3D medical imaging and EHR data. NOTE: this is the first part of release due to PHI review.
DOI: 10.71718/bcyb-k484
title: EchoNet-Tee-View-Classifier

description: Intraoperative TEE videos from approximately 500 unique adult cardiac surgery patients from Stanford University Medical Center. This dataset represents the external test dataset for our TEE view classification study: https://www.nature.com/articles/s41598-023-50735-8
DOI: 10.15468/dl.m8d4nh
title: Occurrence Download

description: A dataset containing 8527 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "and" : [
 "Country is one of (United States of America, United States Minor Outlying Islands, American Samoa, Micronesia (Federated States of), Guam, Marshall Islands, Northern Mariana Islands, Puerto Rico, Palau, Virgin Islands (U.S.))",
 {
 "not" : {
 "Issue" : [
 "is Country coordinate mismatch"
 ]
 }
 }
 ]
 },
 "DatasetKey is one of (Global Register of Introduced and Invasive Species - United States (Contiguous) (ver.2.0, 2022))"
 ]
}

 The dataset includes 8527 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0024624-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.71718/d05h-gy43
title: EchoNet-Pediatric

description: Pediatric echocardiography, or cardiac ultrasound, is the most widely used and readily available imaging modality to assess and manage congenital and acquired heart disease in children. Echocardiography is portable, efficient, and non-invasive, while still providing high quality imaging, making it the foremost frontline diagnostic tool in the United States for cardiac disease. Assessment of left ventricular function is of paramount importance in monitoring disease progression and targeting treatment for a wide range of pediatric diseases, including patients with cancer receiving chemotherapy, arrythmia management, heart failure, post-surgical ventricular function, genetic abnormalities, and acquired heart disease. In addition to our deep learning model, we introduce a new large video dataset of echocardiograms for computer vision research. The EchoNet-Peds database includes 7,643 labeled echocardiogram videos and human expert annotations (measurements, tracings, and calculations) to provide a baseline to study cardiac motion and chamber sizes. The database includes patients ranging from 0-18 years (43% female) with a wide range of sizes.
DOI: 10.15468/dl.s2w5te
title: Occurrence Download

description: A dataset containing 986 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Geoglossum atropurpureum (Batsch) Pers.",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Continent is Europe",
 "CoordinateUncertaintyInMeters is 0,1000",
 "OccurrenceStatus is Present",
 "EventDate is 1960,2024"
 ]
}

 The dataset includes 986 records from 29 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0024626-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.71718/wtrx-wj56
title: EchoNet-LVH

description: Echocardiography, or cardiac ultrasound, is the most widely used and readily available imaging modality to assess cardiac function and structure. Combining portable instrumentation, rapid image acquisition, high temporal resolution, and without the risks of ionizing radiation, echocardiography is one of the most frequently utilized imaging studies in the United States and serves as the backbone of cardiovascular imaging. For diseases ranging from heart failure to valvular heart diseases, echocardiography is both necessary and sufﬁcient to diagnose many cardiovascular diseases. In addition to our deep learning model, we introduce a new large video dataset of echocardiograms (parasternal long axis view) for computer vision research. The EchoNet-LVH dataset includes 12,000 labeled echocardiogram videos and human expert annotations (measurements, tracings, and calculations) to provide a baseline to study cardiac chamber size and wall thickness.
DOI: 10.71718/yqp5-y078
title: EchoNet-Dynamic

description: EchoNet-Dynamic is a dataset of over 10k echocardiogram, or cardiac ultrasound, videos from unique patients at Stanford University Medical Center. Each apical-4-chamber video is accompanied by an estimated ejection fraction, end-systolic volume, end-diastolic volume, and tracings of the left ventricle performed by an advanced cardiac sonographer and reviewed by an imaging cardiologist.
DOI: 10.71718/kqee-3z39
title: DDI - Diverse Dermatology Images

description: Artificial intelligence (AI) may aid in triaging skin diseases. However, most AI models have not been rigorously assessed on images of diverse skin tones or uncommon diseases. To ascertain potential biases in algorithm performance in this context, we curated the Diverse Dermatology Images (DDI) dataset—the first publicly available, deeply curated, and pathologically confirmed image dataset with diverse skin tones. The DDI was retrospectively selected from reviewing pathology reports in Stanford Clinics from 2010-2020 with further details provided in the methods. After filtering out images that were poor quality (see methods), there were a total of 656 images representing 570 unique patients (Supplemental Table 2 and 3). The dataset comprised a retrospective convenience sample across all images of FST I-VI but was also designed to allow direct comparison between FST I-II and FST V-VI by matching diagnostic category, age within 10 years, gender, and date of photograph within 3 years (online methods). There was no significant difference in photo quality scores between FST I-II photos and FST V-VI photos (Mann-Whitney U, p = 0.33). There were a total of 208 images of FST I-II (159 benign, 49 malignant), 241 images of FST III-IV (167 benign, 74 malignant), and 207 images of FST V-VI (159 benign and 48 malignant).
DOI: 10.71718/n3nj-2c03
title: CheXphoto

description: CheXphoto comprises a training set of natural photos and synthetic transformations of 10,507 x-rays from 3,000 unique patients that were sampled at random from the CheXpert training set, and a validation and test set of natural and synthetic transformations applied to all 234 x-rays from 200 patients and 668 x-rays from 500 patients in the CheXpert validation and test sets, respectively.
DOI: 10.71718/y7pj-4v93
title: CheXpert: Chest X-Rays

description: CheXpert is a dataset consisting of 224,316 chest radiographs of 65,240 patients who underwent a radiographic examination at Stanford Health Care between October 2002 and July 2017, in both inpatient and outpatient centers. Included are their associated radiology reports.
DOI: 10.15468/dl.8z79k7
title: Occurrence Download

description: A dataset containing 4111 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Gomphus clavatus (Pers.) Gray",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Continent is Europe",
 "CoordinateUncertaintyInMeters is 0,1000",
 "OccurrenceStatus is Present",
 "EventDate is 1960,2024"
 ]
}

 The dataset includes 4111 records from 32 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0024628-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.71718/6nvz-pm34
title: CheXpert Plus

description: The CheXpert Plus dataset is a comprehensive collection that brings together text and images in the medical field, featuring a total of 223,462 unique pairs of radiology reports and chest X-rays across 187,711 studies from 64,725 patients. This dataset is notable for its organization and depth, with each patient potentially linked to multiple studies, and each study possibly including several chest X-rays. The X-rays are provided in DICOM format, including 47 DICOM metadata elements to support detailed analysis. Accompanying these images are 187,711 radiology reports, each meticulously divided into 11 subsections for thorough examination. Finally, the dataset is enriched with annotations for 14 different chest pathologies across the studies, alongside 8 metadata elements concerning patient information. The curation and release of this dataset was supported in part by the Medical Imaging and Data Resource Center (MIDRC), which is funded by the National Institute of Biomedical Imaging and Bioengineering (NIBIB) of the National Institutes of Health under contract 75N92020D00021 and through The Advanced Research Projects Agency for Health (ARPA-H).
DOI: 10.5281/zenodo.11454945
title: North Atlantic EXtratropical CYCLONE TRAcks and Lagrangian-Derived MOisture Uptake Dataset: ExCyclone-TRAMO (Part I)

description: Abstract:

This dataset focuses on extratropical cyclones (ETCs) over the North Atlantic Ocean (NATL) during the extended winter seasons, spanning from October to April, between 1985 and 2022. The relationship between moisture uptake and precipitation in various mesoscale ETC structures remains an active research area. The provision of moisture parameters through tracer dispersion models enhances our understanding of moisture dynamics, the behaviour of ETCs, and the associated meteorological fields.

Description:

The dataset was constructed through dynamic downscaling of ERA5 reanalysis data using the Weather Research and Forecasting (WRF) model, in conjunction with the Lagrangian dispersion model FELXPART-WRF. It consists of 6-hourly time intervals with a horizontal resolution of 0.18°. This database is completely described in Coll-Hidalgo, P., Gimeno-Sotelo, L., Fernández-Alvarez, J.C. et al. North Atlantic Extratropical Cyclone Tracks and Lagrangian-Derived Moisture Uptake Dataset. Sci Data 11, 1258 (2024). https://doi.org/10.1038/s41597-024-04091-5

The dataset includes:



Detailed tracking of ETCs across the North Atlantic:



Date in year-month-day format

hh (in UTC): Hour in Coordinated Universal Time

latitude (degrees north): Latitude in degrees north

longitude (degrees west): Longitude in degrees west

MSLP (hPa): Mean sea level pressure in hectopascals (hPa)

Radius (km): Cyclone radius in kilometres (km)

Last closed isobar (hPa): Pressure at the last closed isobar in hectopascals (hPa)

Low-level thermal wind parameter (VTL)

High-level thermal wind parameter (VTU)

The thermal asymmetry parameter (B)






Two-Dimensional Masks Shaping ETCs:



Radius

Warm Conveyor Belt (WCB) footprint Related Areas

A theoretical boundary encompassing a broader extent of the ETC circulation within a spiral shape 






Cyclone Moisture Uptake-Related Variables by ETCs life timesteps: 



Total moisture uptake

Discrete Moisture Uptake (10-Day Backward)

Moisture uptake by layers from the surface to 100 hPa.




Dataset Repository Information

This repository contains the dataset for the years 1985-1999. For users interested in datasets from subsequent periods, please refer to the following links:

Years 2000-2014: Access the dataset hereYears 2015-2022: Access the dataset here

A GitHub repository is available, providing example code that demonstrates how to use and handle the dataset effectively.
DOI: 10.5281/zenodo.13844378
title: North Atlantic EXtratropical CYCLONE TRAcks and Lagrangian-Derived MOisture Uptake Dataset: ExCyclone-TRAMO (Part I)

description: Abstract:

This dataset focuses on extratropical cyclones (ETCs) over the North Atlantic Ocean (NATL) during the extended winter seasons, spanning from October to April, between 1985 and 2022. The relationship between moisture uptake and precipitation in various mesoscale ETC structures remains an active research area. The provision of moisture parameters through tracer dispersion models enhances our understanding of moisture dynamics, the behaviour of ETCs, and the associated meteorological fields.

Description:

The dataset was constructed through dynamic downscaling of ERA5 reanalysis data using the Weather Research and Forecasting (WRF) model, in conjunction with the Lagrangian dispersion model FELXPART-WRF. It consists of 6-hourly time intervals with a horizontal resolution of 0.18°. This database is completely described in Coll-Hidalgo, P., Gimeno-Sotelo, L., Fernández-Alvarez, J.C. et al. North Atlantic Extratropical Cyclone Tracks and Lagrangian-Derived Moisture Uptake Dataset. Sci Data 11, 1258 (2024). https://doi.org/10.1038/s41597-024-04091-5

The dataset includes:



Detailed tracking of ETCs across the North Atlantic:



Date in year-month-day format

hh (in UTC): Hour in Coordinated Universal Time

latitude (degrees north): Latitude in degrees north

longitude (degrees west): Longitude in degrees west

MSLP (hPa): Mean sea level pressure in hectopascals (hPa)

Radius (km): Cyclone radius in kilometres (km)

Last closed isobar (hPa): Pressure at the last closed isobar in hectopascals (hPa)

Low-level thermal wind parameter (VTL)

High-level thermal wind parameter (VTU)

The thermal asymmetry parameter (B)






Two-Dimensional Masks Shaping ETCs:



Radius

Warm Conveyor Belt (WCB) footprint Related Areas

A theoretical boundary encompassing a broader extent of the ETC circulation within a spiral shape 






Cyclone Moisture Uptake-Related Variables by ETCs life timesteps: 



Total moisture uptake

Discrete Moisture Uptake (10-Day Backward)

Moisture uptake by layers from the surface to 100 hPa.




Dataset Repository Information

This repository contains the dataset for the years 1985-1999. For users interested in datasets from subsequent periods, please refer to the following links:

Years 2000-2014: Access the dataset hereYears 2015-2022: Access the dataset here

A GitHub repository is available, providing example code that demonstrates how to use and handle the dataset effectively.
DOI: 10.71718/6dj3-2097
title: CheXpert Demo Data

description: Recent work has found that deep learning models can trivially predict self-reported race on medical imaging datasets including CheXpert. We are providing the self-reported race labels for the popular CheXpert dataset in the interest of open science, experimental validation and reproducibility, and to encourage further work in this important area.
DOI: 10.71718/hap9-kn94
title: CheXlocalize

description: CheXlocalize is a radiologist-annotated segmentation dataset on chest X-rays. The dataset consists of two types of radiologist annotations for the localization of 10 pathologies: pixel-level segmentations and most-representative points. Annotations were drawn on images from the CheXpert validation and test sets. The dataset also consists of two separate sets of radiologist annotations: (1) ground-truth pixel-level segmentations on the validation and test sets, drawn by two board-certified radiologists, and (2) benchmark pixel-level segmentations and most-representative points on the test set, drawn by a separate group of three board-certified radiologists. The validation and test sets consist of 234 chest X-rays from 200 patients and 668 chest X-rays from 500 patients, respectively. The 10 pathologies of interest were Atelectasis, Cardiomegaly, Consolidation, Edema, Enlarged Cardiomediastinum, Lung Lesion, Lung Opacity, Pleural Effusion, Pneumothorax, and Support Devices. For more details, please see: https://github.com/rajpurkarlab/cheXlocalize.
DOI: 10.71718/jn0r-7p52
title: CT Pulmonary Angiography

description: A collection of CT pulmonary angiography (CTPA) for patients susceptible to Pulmonary Embolism (PE). In addition to slice-level PE labels, we provide labels for PE location, RV/LV ratio, and PE type.
DOI: 10.71718/ge5g-ds80
title: COCA - Coronary Calcium and Chest CTs

description: We provide two datasets: 1) gated coronary CT DICOM images with corresponding coronary artery calcium segmentations and scores (xml files) 2) non-gated chest CT DICOM images with coronary artery calcium scores
DOI: 10.15468/dl.jcwuen
title: Occurrence Download

description: A dataset containing 853 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Hapalopilus croceus (Pers.) Donk",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Continent is Europe",
 "CoordinateUncertaintyInMeters is 0,1000",
 "OccurrenceStatus is Present",
 "EventDate is 1960,2024"
 ]
}

 The dataset includes 853 records from 16 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0024629-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.