Loading...
Loading...
Medical imaging (X-ray, CT, MRI), electronic health records, clinical trials, ECG/EEG, pathology
13,161 datasets
A retrospective cohort of pediatric patients admitted with abdominal pain to Children's Hospital St. Hedwig in Regensburg, Germany. The dataset includes multiple abdominal B-mode ultrasound images per patient, alongside laboratory tests, physical examination results, and clinical scores like Alvarado and pediatric appendicitis scores. Subjects are labeled for diagnosis, management, and severity of appendicitis.
Clinical data from the PhysioNet/Computing in Cardiology Challenge 2019, focused on the early detection of sepsis. The dataset was created by Matthew Reyna et al. and is licensed under PhysioNet. The description cites significant public health statistics, including an estimated 30 million global sepsis cases annually.
2,126 fetal cardiotocograms (CTGs) were automatically processed and their diagnostic features measured. The CTGs were classified by three expert obstetricians, with consensus labels assigned for both morphologic patterns (A, B, C, etc.) and fetal states (Normal, Suspect, Pathologic). The dataset was created by Ayres-de-Campos et al. and is available via OpenML.
A retrospective cohort of pediatric patients admitted with abdominal pain to Children's Hospital St. Hedwig in Regensburg, Germany. The dataset includes multiple abdominal B-mode ultrasound images per patient, alongside laboratory tests, physical exams, clinical scores, and expert ultrasonographic findings. Subjects are labeled with three target variables: diagnosis, management, and severity.
418 patients with primary biliary cirrhosis from a Mayo Clinic study between 1974 and 1984, with data on survival, drug trial participation, and clinical measurements. The dataset was created by authors E. Dickson, P. Grambsch, T. Fleming, L. Fisher, and A. Langworthy. It includes 20 features per patient, such as lab results and disease stage, after preprocessing steps like imputation and one-hot encoding.
858 patient records from 'Hospital Universitario de Caracas' in Caracas, Venezuela, comprise this dataset for multilabel classification. It includes demographic information, habits, and historic medical records, collected by Kelwin Fernandes, Jaime S. Cardoso, and Jessica Fernandes. Several patients decided not to answer some questions, resulting in missing values.
Hospital Universitario de Caracas in Venezuela collected demographic, habit, and medical history data from 858 patients to study cervical cancer risk. The dataset includes attributes such as age, sexual history, pregnancies, smoking, contraceptive use, and STDs, with a binary target variable derived from four diagnostic tests. It was contributed by researchers Kelwin Fernandes, Jaime S. Cardoso, and Jessica Fernandes.
The dataset originates from the PhysioNet/Computing in Cardiology Challenge 2019, created by Matthew Reyna et al. It focuses on sepsis, a life-threatening condition causing significant global morbidity and mortality. The data is intended to address fundamental questions about the limits of early sepsis detection and treatment.
The dataset originates from the PhysioNet/Computing in Cardiology Challenge 2019, created by Matthew Reyna et al. It focuses on sepsis, a life-threatening condition causing significant global morbidity and mortality. The data is intended to address fundamental questions about the limits of early sepsis detection and treatment.
2,126 fetal cardiotocograms (CTGs) were automatically processed and their diagnostic features measured. The CTGs were classified by three expert obstetricians, with consensus labels assigned for both morphologic patterns (A, B, C, etc.) and fetal states (Normal, Suspect, Pathologic). The dataset was created by Ayres-de-Campos et al. and is available via OpenML.
2126 fetal cardiotocograms (CTGs) were automatically processed and diagnostic features measured. The CTGs were classified by three expert obstetricians, with consensus labels assigned for both morphologic patterns and fetal states. The dataset was created by Ayres-de-Campos et al. and is available via OpenML.
A retrospective cohort dataset from pediatric patients admitted with abdominal pain to Children's Hospital St. Hedwig in Regensburg, Germany. It includes multiple abdominal B-mode ultrasound images, laboratory tests, physical examination results, clinical scores, and expert ultrasonographic findings for each subject. Subjects are labeled with three target variables: diagnosis, management, and severity of appendicitis.
858 patient records from 'Hospital Universitario de Caracas' in Caracas, Venezuela, comprise this dataset for multilabel classification. It includes demographic information, habits, and historic medical records, collected by Kelwin Fernandes, Jaime S. Cardoso, and Jessica Fernandes. Several patients decided not to answer some questions, resulting in missing values.
National incidence estimates for approximately 700,000 nonfatal injury and poisoning cases treated in U.S. hospital emergency departments in 2023. It is collected from a stratified probability sample of hospitals and includes variables such as age, principal diagnosis, body part affected, and injury intent. The data is managed by the U.S. Consumer Product Safety Commission and the CDC's National Center for Injury Prevention and Control.
National incidence estimates for approximately 700,000 nonfatal injury and poisoning cases treated in U.S. hospital emergency departments annually. It is collected from a stratified probability sample of hospitals and includes variables such as age, principal diagnosis, body part affected, and injury intent. The data is managed by the U.S. Consumer Product Safety Commission and the CDC's National Center for Injury Prevention and Control.
Sample hospital data published on the Kaggle platform. The dataset's specific content, scale, and origin are not detailed in the available metadata. Further inspection after download is required to confirm its structure and potential applications.
Healthcare emergency dataset published on Kaggle. The dataset's specific content, size, and origin are not detailed in the available metadata. Its actual scope and quality require verification after download.
A collection of digital knee X-ray images hosted on Kaggle. The dataset likely contains medical images of knee joints, which are commonly used for diagnostic purposes. Specific details regarding the number of images, collection dates, and originating institution are not provided in the available metadata.
IU X-Ray is a dataset of medical X-ray images published on Kaggle. The specific anatomical focus, collection size, and creation details are not provided in the available metadata. Users must download the dataset to verify its exact content and scope.
Kaggle hosts a dataset titled 'healthcare_disease'. The dataset's content likely pertains to disease-related information within the healthcare domain. Specific details regarding its size, origin, and creation date are unavailable from the provided metadata.