Data

The database includes 154 conventional chest radiographs with a lung nodule (100 malignant and 54 benign nodules) and 93 radiographs without a nodule  The database also includes additional information such as; patient age, gender, diagnosis (malignant or benign), X and Y coordinates of nodule, simple diagram of nodule location. Lung nodule images were classified into five groups according to the degrees of subtlety.

Related publication:  Shiraishi J, Katsuragawa S, lkezoe J, et al: Development of a digital image database for chest radiographs with and without a lung nodule: Receiver operating characteristic analysis of radiologists’ detection of pulmonary nodules. AJR 174:71-74, 2000.

Data was collected from nine healthy volunteers during a study of propofol-induced unconsciousness.  For all subjects, approximately 3 hours of data were recorded while using target-controlled infusion protocol.Data includes continuous electrocardiogram (ECG); interventions included in the study for patient safety, such as administering phenylephrine (a vasopressor);heart rate variability (HRV) and electrodermal activity (EDA).

Related publication: Subramanian, S., Purdon, P., Barbieri, R., & Brown, E. (2021). Behavioral and autonomic dynamics during propofol-induced unconsciousness (version 1.0). PhysioNet. https://doi.org/10.13026/2rbc-1r03.

The PTB-XL ECG dataset is a large dataset of 21837 clinical 12-lead ECGs from 18885 patients of 10 second length. The raw waveform data was annotated by up to two cardiologists, who assigned potentially multiple ECG statements to each record. Total 71 different ECG statements conform to the SCP-ECG standard and cover diagnostic, form, and rhythm statements.

Related publications: Wagner, P., Strodthoff, N., Bousseljot, R.-D., Kreiseler, D., Lunze, F.I., Samek, W., Schaeffter, T. (2020), PTB-XL: A Large Publicly Available ECG Dataset. Scientific Data. https://doi.org/10.1038/s41597-020-0495-6

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. It has a total of 656 images representing 570 unique patients.

Datasets is a library for easily accessing and sharing datasets, and evaluation metrics for Natural Language Processing (NLP), computer vision, and audio tasks.Currently over 2658 datasets, and more than 34 metrics available.At least 13 datasets with “medical” term search.Load a dataset in a single line of code, and use our powerful data processing methods to quickly get your dataset ready for training in a deep learning model.

The DCSM dataset consists of 255 randomly selected and fully anonymized overnight lab-based PSG recordings from patients visiting the DCSM for the diagnosis of non-specific sleep related disorders. The DCSM dataset represents a diverse cohort of Danish patients with respect to demographic characteristics, diagnostic background and sleep/non-sleep related medication usage, collected between 2015-2018.

Two publicly-available datasets, DOD-H including 25 healthy volunteers and DOD-O including 55 patients suffering from obstructive sleep apnea (OSA). Both datasets have been scored by 5 sleep technologists from different sleep centers. We developed a framework to compare automated approaches to a consensus of multiple human scorers.

Related publication: A. Guillot, F. Sauvet, E. H. During and V. Thorey, “Dreem Open Datasets: Multi-Scored Sleep Datasets to Compare Human and Automated Sleep Staging,” in IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol. 28, no. 9, pp. 1955-1965, Sept. 2020, doi: 10.1109/TNSRE.2020.3011181.

375 heterogeneous cardiac magnetic resonance (CMR) datasets acquired by using four different scanner vendors in six hospitals and three different countries (Spain, Canada and Germany).

Related publication: V. M. Campello et al., “Multi-Centre, Multi-Vendor and Multi-Disease Cardiac Segmentation: The M&Ms Challenge,” in IEEE Transactions on Medical Imaging, vol. 40, no. 12, pp. 3543-3554, Dec. 2021, doi: 10.1109/TMI.2021.3090082.

TCIA data are organized as “collections”; typically these are patient cohorts related by a common disease (e.g. lung cancer), image modality or type (MRI, CT, digital histopathology, etc) or research focus. Supporting data related to the images such as patient outcomes, treatment details, genomics and image analyses are also provided when available. Over  100+ datasets, many of which are public.

Unstructured notes from the Research Patient Data Registry at Partners Healthcare,Boston,USA (originally developed during the i2b2 project). Clinical Natural Language Processing (NLP) data sets were originally created at a former NIH-funded National Center for Biomedical Computing (NCBC) known as i2b2: Informatics for Integrating Biology and the Bedside. Beginning in 2018, they are officially known as n2c2 (National NLP Clinical Challenges).

A publicly available EMR Question Answering (QA) corpus by creating a large-scale dataset, emrQA, using a novel semi-automated generation framework that allows for minimal expert involvement and re-purposes existing annotations available for other clinical NLP tasks.EmrQA has 1 million question-logical form and 400,000+ question answer evidence pairs. The dataset uses existing NLP task annotations from the i2b2 Challenge datasets.

Related publication: Pampari, A., Raghavan, P., Liang, J.J., & Peng, J. (2018). emrQA: A Large Corpus for Question Answering on Electronic Medical Records. EMNLP.

VSCapture, an open source tool developed in C# programming language on the .NET/Mono platform that allows the tool to run on Windows, Macintosh OS X, Linux Ubuntu operating systems.

Related Publication: Data acquisition from S/5 GE Datex anesthesia monitor using VSCapture.

Related Dataset: The University of Queensland Vital Signs Dataset.

The University of Queensland Vital Signs Dataset contains a wide range of patient monitoring data and vital signs that were recorded during 32 surgical cases where patients underwent anaesthesia at the Royal Adelaide Hospital.

12,625 whole-slide images (WSIs) of prostate biopsies were available for model development (the development set), 393 for performance evaluation during the competition phase (the tuning set), 545 as the internal validation set in the postcompetition phase and 1,071 for external validation from 6 different sites.

Related publication: Bulten, W., Kartasalo, K., Chen, PH.C. et al. Artificial intelligence for diagnosis and Gleason grading of prostate cancer: the PANDA challenge. Nat Med (2022). https://doi.org/10.1038/s41591-021-01620-2

This is a dataset from tertiary care medical college and hospital in India’s cardiology unit which had 14,845 admissions corresponding to 12,238 patients.

Related publication: Bollepalli, S.C.; Sahani, A.K.; Armoundas, A.A. ,et al. An Optimized Machine Learning Model Accurately Predicts In-Hospital Outcomes at Admission to a Cardiac Unit. Diagnostics 2022, 12, 241.

https://doi.org/10.3390/diagnostics12020241

The dataset included over 69,000 dermatology images.International Skin Imaging Collaboration (ISIC) is a global partnership that has organized the world’s largest repository of publicly available dermoscopic images, hosted the first public benchmarks for melanoma detection in dermoscopic images, titled “Skin Lesion Analysis Towards Melanoma Detection”, at the IEEE International Symposium of Biomedical Imaging (ISBI).

A dataset of 491 Head CT scans with 193,317 slices, anonymized dicoms for all the scans and the corresponding radiologists’ reads done by three radiologists with an experience of 8, 12 and 20 years in cranial CT interpretation respectively.

Related publication: Development and Validation of Deep Learning Algorithms for Detection of Critical Findings in Head CT scan.

Publicly available  suite of tailored deep neural network models for tackling different challenges ranging from screening to risk stratification to treatment planning for patients with the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). 

• Chest x-rays: 16,352 CXR images across 14,979 patients Click here
• Chest CT: 201,103 CT slices from 4,501 patients Click here
• Chest point-of-care ultrasound: 29,651 POCUS images Click here
• COVID-Net ICU:1925 records from 385 patients   Click here

Also,expanded to open source TB-Net initiative for tuberculosis screening, Fibrosis-Net initiative for pulmonary fibrosis progression prediction, and Cancer-Net initiative for cancer screening.

MIMIC-ED is a large, freely available database of emergency department (ED) admissions at the Beth Israel Deaconess Medical Center between 2011 and 2016. 448,972 ED stays with vital signs, triage information, medication reconciliation, medication administration, and discharge diagnoses available

Chest X-ray dataset with eye tracking and report dictation. Built on MIMIC Chest X-ray dataset.1,083 CXR images.

Related publication:

Karargyris, A., Kashyap, S., Lourentzou, I. et al. Creation and validation of a chest X-ray dataset with eye-tracking and report dictation for AI development.Sci Data 8, 92 (2021).

This database is the first multi-institutional, multi-national expert annotated COVID-19 imaging dataset.Annotated by three radiologists with majority vote adjudication by board certified radiologists,RICORD consists of 240 thoracic CT scans and 1,000 chest radiographs contributed from four international sites.

A comprehensive dataset of 6,388 surgical patients composed of intraoperative biosignals and clinical information from the Department of Anesthesiology and Pain Medicine, Seoul National University College of Medicine, Seoul, Korea .

The NuCLS dataset contains over 220,000 labeled nuclei from breast cancer images from The Cancer Genome Atlas( TCGA). These nuclei were annotated through the collaborative effort of pathologists, pathology residents, and medical students.

CheXpert is a  public dataset for chest radiograph interpretation, consisting of 224,316 chest radiographs of 65,240 patients from Stanford Hospital.

The GDC Portal is a platform from National Cancer Institute(NCI) with cancer related genomic data for 80,000+ cases.

Annotations by CARING’s (Centre for Advanced research in Imaging, Neuroscience and Genomics) expert radiologists on COVID-19 positive X-rays.The corresponding X-rays were released by Medical Imaging Data Bank of the Valencia region (BIMCV).

BIMCV-COVID19+ dataset is a large dataset with chest X-ray images  and computed tomography (CT) imaging of COVID-19 patients along with their radiographic findings, pathologies, polymerase chain reaction (PCR), immunoglobulin antibody tests and radiographic reports from Medical Imaging Databank in Valencian Region Medical Image Bank (BIMCV).These iterations of the database include 7377 CR, 9463 DX and 6687 CT studies.

Provided on Kaggle by the Vingroup Big Data Institute (VinBigData) aims to promote fundamental research and investigate novel and highly-applicable technologies.A dataset consisting of 18,000 images that have been annotated by experienced radiologists.

The EchoNet-Dynamic database includes 10,030 labeled echocardiogram videos and human expert annotations (measurements, tracings, and calculations) to provide a baseline to study cardiac motion and chamber sizes

941 sentences from 911 PubMed abstracts, annotated with PGx entities of interest (mainly genes variations, gene, drugs and phenotypes), and relationships between those.

40+ speciality classified list of open source datasets for healthcare with direct links to the datasets and more information.

More than a 100 healthcare related datasets from around the world, classified and annotated.

Dataset created for the purpose of continuing research into COVID-19. However with information from all 50 states and the District of Columbia, many US statistics can be compared.

The DILIrank dataset is an updated version of the LTKB Benchmark dataset. DILIrank consists of 1,036 FDA-approved drugs that are divided into four classes according to their potential for causing drug-induced liver injury (DILI).

Dataset for automatically segmenting and classifying corneal ulcers with 712 ocular staining images and the associated segmentation labels for flaky corneal ulcers.

4000+ healthcare datasets made available from Harvard University.Searchable and diverse.

Semi automatically generated nuclei instance segmentation and classification dataset with exhaustive nuclei labels across 19 different tissue types. The dataset consists of 481 visual fields, of which 312 are randomly sampled from more than 20K whole slide images at different magnifications, from multiple data sources.

A dataset with Images,mainly Chest X-rays from COVID-19 patients.

Multiple data sources for COVID-19 in a unified data model, ready for analysis at one place.

In response to the COVID-19 pandemic, the White House and a coalition of leading research groups have prepared the COVID-19 Open Research Dataset (CORD-19). CORD-19 is a resource of over 29,000 scholarly articles, including over 13,000 with full text, about COVID-19, SARS-CoV-2, and related coronaviruses.

This dataset has daily level information on the number of affected cases, deaths and recovery from 2019 novel coronavirus.

The data is available since 22 Jan, 2020.

Largest collection of Intracranial hemorrhage CT scans.874 035 images with expert annotations.

Reference: Construction of a Machine Learning Dataset through Collaboration: The RSNA 2019 Brain CT Hemorrhage Challenge

One of the most comprehensive source of many datasets in healthcare.Primarily from ICU patients.

https://physionet.org/about/database/

MIMIC – IV Dataset (https://physionet.org/content/mimiciv/0.4/)

Includes:

• Clinical datasets such as MIMIC,eICU collaborative and Pediatic ICU datasets.
• Waveform datasets with ECG,EEG,arterial blood pressure waveform.
• ECG datasets with various pathophysiologic changes and drug interactions.
• Fetal datasets including sounds and ECG.
• Gait and Balance datasets include gait dynamics for patients with various neurodegenerative disorders.
• Neuro and Myoelectic datasets with EEG,EMG and evoked potential waveforms.
• Image datasets with Chest X-rays and MRI images.
• Computed Tomography Images for Intracranial Hemorrhage Detection and Segmentation
• Miscellaneous datasets with text, language,posture and other datasets

Alzheimer’s disease patient’s imaging(MRI), clinical, genomic, and biomarker data for the purposes of scientific investigation, teaching, or planning clinical research studies.

http://adni.loni.usc.edu/data-samples/access-data/

RIM-ONE is a database for optic disc and cup segmentation evaluation by Medical Image Analysis group.

Contains data related to 23,376 intensive care unit and high dependency unit admissions at Amsterdam University Medical Center of adult patients from 2003-2016.

The FDA Adverse Event Reporting System (FAERS) is a database that contains adverse event reports, medication error reports and product quality complaints resulting in adverse events that were submitted to FDA

A repository of segmented cells from the thin blood smear slide images from the Malaria Screener research activity.The dataset contains a total of 27,558 cell images with equal instances of parasitized and uninfected cells.

1200 Retinal image dataset with annotation.

A de-identified dataset of retinal fundus images for glaucoma analysis (RIGA) derived from three sources with 750 original images and 4500 manual marked images

The public database contains 15 images of healthy patients, 15 images of patients with diabetic retinopathy and 15 images of glaucomatous patients.

39 images for development of vessel extraction algorithms suitable for retinal screening programmes.

Datasets from National Cancer Institute of over 54000 patients. They include data on participant characteristics, screening exam results, diagnostic procedures, lung cancer, and mortality. Images from over 75,000 CT screening exams are available. Over 1,200 pathology images from a subset of NLST lung cancer patients (~500 of over 2,000 patients) may be viewed.

Polysomnography dataset from NSRR for sleep studies.Large collection of deidentified physiologic signals perfect for ML development.

A large collection of multi-source dermatoscopic images of common pigmented skin lesions containing 10000 images.

Related publication:The HAM10000 dataset, a large collection of multi-source dermatoscopic images of common pigmented skin lesions

This open source repository has more than 400 datasets including healthcare(100+) and non-healthcare ones in searchable and categorized format.

CMS datasets provide US Medicare and Medicaid datasets.

ResDAC(The Research Data Assistance Center) provides free support to users of CMS datasets.Link:  https://www.resdac.org/learn

Center for Disease Control’s datasets.Useful for incidence,prevalance of various disorders and mortality data from across the US.

Agency for Healthcare Research and Quality’s HCUP datasets used to identify, track, and analyze US national trends in health care utilization, access, charges, quality, and outcomes.

UK government’s National Health services datasets.NHS choices datasets are useful for NLP and sentiment analysis both for GPs and hospitals.

Brain MRI datasets from Open Accesss series of Imaging Studies(OASIS).

A free and open platform for sharing MRI, MEG, EEG, iEEG, and ECoG data with over 200 datasets.

Cancer epidemiology data available through NCI’s Surveillance,Epidemiology and End Result Program(SEER).

Cancer and genomics datasets.

A dataset of 14,000+ anonymized, radiologist labeled musculoskeletal X-rays from 12,000+ patients from Stanford ML group.

Related publication: https://arxiv.org/abs/1712.06957

1500+ knee MRI anonymized dataset from NYU.

One stop to learn Natural Language processing and more.

Related publication: Bird, Steven, Edward Loper and Ewan Klein (2009), Natural Language Processing with Python. O’Reilly Media Inc.

An excellent resource for trends and updates in AI, especially NLP by Elvis Saravia.

An excellent collection of articles on data science.

Google’s powerful search engine to assist with dataset search.

Over 100,000 anonymized chest x-ray images and their corresponding data from more than 30,000 patients, including many with advanced lung disease.

NIH release of  a dataset containing 32,000 CT scan images with annotated lesions  belonging to 4400 unique patients.

A CMS initiative to democratize research and development using beneficiary data.Greater than 70 million patient dataset available.

The link below is for NIH’s strategic plan for data science in healthcare.A must read for anyone using data in healthcare for research and innovation

Largest open source Chest X-Ray data set available through NIH’s clinical center.See the link in the article to access the data.Also available through GITHUB and KAGGLE.

One of the the largest and most advanced software development platform in the world with many datasets and repositories.

Kaggle is a great resource for de-identified datasets in healthcare.

A biomedical data search engine which searches for datasets across registries.

A place to store, share or find data.A platform for biomedical  research.

Detailed data repositories for biomedical research especially proteins and genetics.