Physicians (per 1,000 people) in Papua New Guinea was reported at 0.063 in 2021, according to the World Bank collection of development indicators, compiled from officially recognized sources. Papua New Guinea - Physicians - actual values, historical data, forecasts and projections were sourced from the World Bank on September of 2025.

Spine MRI Dataset, Fracture Detection, Anomaly Detection & Segmentation

The dataset consists of .dcm files containing MRI scans of the spine of the person with several dystrophic changes, such as osteochondrosis, spondyloarthrosis, hemangioma, physiological lordosis smoothed, osteophytes and aggravated defects. The images are labeled by the doctors and accompanied by report in PDF-format.

The dataset includes 9 studies, made from the different angles which provide a comprehensive understanding of a several dystrophic changes and useful in training spine anomaly classification algorithms. Each scan includes detailed imaging of the spine, including the vertebrae, discs, nerves, and surrounding tissues.

MRI study angles in the dataset

https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F12421376%2F62acce9c1d60720bdd396e036718f406%2FFrame%2084.png?generation=1708543957118470&alt=media" alt="">

💴 For Commercial Usage: Full version of the dataset includes 20,000 spine studies of people with different conditions, leave a request on TrainingData to buy the dataset

Types of diseases and conditions in the full dataset:

• Degeneration of discs
• Osteophytes
• Osteochondrosis
• Hemangioma
• Disk extrusion
• Spondylitis
• AND MANY OTHER CONDITIONS

https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F12421376%2Fd2f21b9ac7dc26a3554e4647db47df57%2F3.gif?generation=1708543677763656&alt=media" alt="">

Researchers and healthcare professionals can use this dataset to study spinal conditions and disorders, such as herniated discs, spinal stenosis, scoliosis, and fractures. The dataset can also be used to develop and evaluate new imaging techniques, computer algorithms for image analysis, and artificial intelligence models for automated diagnosis.

OTHER MEDICAL SPINE MRI DATASETS:

• Spine MRI Dataset -Anomaly Detection
• Spine Segmentation Dataset - MRI Images
• Spinal Vertebrae Segmentation Dataset
• Spine Magnetic Resonance Imaging Dataset

💴 Buy the Dataset: This is just an example of the data. Leave a request on https://trainingdata.pro/datasets to discuss your requirements, learn about the price and buy the dataset

Content

The dataset includes:

• ST000001: includes subfolders with 9 studies. Each study includes MRI-scans in .dcm and .jpg formats,
• DICOMDIR: includes information about the patient's condition and links to access files,
• Spine_MRI_2.pdf: includes medical report, provided by the radiologist,
• .csv file: includes id of the studies and the number of files

Medical reports include the following data:

• Patient's demographic information,
• Description of the case,
• Preliminary diagnosis,
• Recommendations on the further actions

All patients consented to the publication of data

Medical data might be collected in accordance with your requirements.

TrainingData provides high-quality data annotation tailored to your needs

keywords: visual, label, positive, negative, symptoms, clinically, sensory, varicella, syndrome, predictors, diagnosed, rsna cervical, image train, segmentations meta, spine train, mri spine scans, spinal imaging, radiology dataset, neuroimaging, medical imaging data, image segmentation, lumbar spine mri, thoracic spine mri, cervical spine mri, spine anatomy, spinal cord mri, orthopedic imaging, radiologist dataset, mri scan analysis, spine mri dataset, machine learning medical imaging, spinal abnormalities, image classification, neural network spine scans, mri data analysis, deep learning medical imaging, mri image processing, spine tumor detection, spine injury diagnosis, mri image segmentation, spine mri classification, artificial intelligence in radiology, spine abnormalities detection, spine pathology analysis, mri feature extraction, tomography, cloud

COVID19-Algeria-and-World-Dataset

A coronavirus dataset with 104 countries constructed from different reliable sources, where each row represents a country, and the columns represent geographic, climate, healthcare, economic, and demographic factors that may contribute to accelerate/slow the spread of the COVID-19. The assumptions for the different factors are as follows:

• Geography: some continents/areas may be more affected by the disease
• Climate: cold temperatures may promote the spread of the virus
• Healthcare: lack of hospital beds/doctors may lead to more human losses
• Economy: weak economies (GDP) have fewer means to fight the disease
• Demography: older populations may be at higher risk of the disease

The last column represents the number of daily tests performed and the total number of cases and deaths reported each day.

Data description

https://raw.githubusercontent.com/SamBelkacem/COVID19-Algeria-and-World-Dataset/master/Images/Data%20description.png">

Countries in the dataset by geographic coordinates

https://raw.githubusercontent.com/SamBelkacem/COVID19-Algeria-and-World-Dataset/master/Images/Countries%20by%20geographic%20coordinates.png">

• Europe: 33 countries
• Asia: 28 countries
• Africa: 21 countries
• North America: 11 countries
• South America: 8 countries
• Oceania: 3 countries

Statistical description of the data

https://raw.githubusercontent.com/SamBelkacem/COVID19-Algeria-and-World-Dataset/master/Images/Statistical%20description%20of%20the%20data.png">

Data distribution

https://raw.githubusercontent.com/SamBelkacem/COVID19-Algeria-and-World-Dataset/master/Images/Data%20distribution.png">

Download

The dataset is available in an encoded CSV form on GitHub.

Python code

The Python Jupyter Notebook to read and visualize the data is available on nbviewer.

Data update

The dataset is updated every month with the latest numbers of COVID-19 cases, deaths, and tests. The last update was on March 01, 2021.

Data construction

The dataset is constructed from different reliable sources, where each row represents a country, and the columns represent geographic, climate, healthcare, economic, and demographic factors that may contribute to accelerate/slow the spread of the coronavirus. Note that we selected only the main factors for which we found data and that other factors can be used. All data were retrieved from the reliable Our World in Data website, except for data on:

• Continents: www.kaggle.com/statchaitya/country-to-continent
• Geographic-coordinates: www.kaggle.com/eidanch/counties-geographic-coordinates
• Temperatures: www.kaggle.com/berkeleyearth/climate-change-earth-surface-temperature-data
• Share of the population over 65 years old: https://data.worldbank.org/indicator/SP.POP.65UP.TO.ZS
• GDP/Capita: https://data.worldbank.org/indicator/NY.GDP.PCAP.CD

Citation

If you want to use the dataset please cite the following arXiv paper, more details about the data construction are provided in it.

@article{belkacem_covid-19_2020,
  title = {COVID-19 data analysis and forecasting: Algeria and the world},
  shorttitle = {COVID-19 data analysis and forecasting},
  journal = {arXiv preprint arXiv:2007.09755},
  author = {Belkacem, Sami},
  year = {2020}
}

Contact

If you have any question or suggestion, please contact me at this email address: s.belkacem@usthb.dz

Spine MRI Dataset, Fracture Detection & Segmentation

The dataset consists of .dcm files containing MRI scans of the spine of the person with several dystrophic changes, such as osteophytes, focal mass in the Th7 vertebral body, fluid mass on the anterior contour of the Th7 vertebra, dorsal protrusion of the Th11-Th12 disc and spondyloarthrosis. The images are labeled by the doctors and accompanied by report in PDF-format.

The dataset includes 5 studies, made from the different angles which provide a comprehensive understanding of a several dystrophic changes and useful in training spine anomaly classification algorithms. Each scan includes detailed imaging of the spine, including the vertebrae, discs, nerves, and surrounding tissues.

MRI study angles in the dataset

https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F12421376%2F194ff0a2f385675e893fdcf35878de74%2FFrame%2086.png?generation=1709116584443420&alt=media" alt="">

💴 For Commercial Usage: Full version of the dataset includes 20,000 spine studies of people with different conditions, leave a request on TrainingData to buy the dataset

Types of diseases and conditions in the full dataset:

• Degeneration of discs
• Osteophytes
• Osteochondrosis
• Hemangioma
• Disk extrusion
• Spondylitis
• AND MANY OTHER CONDITIONS

https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F12421376%2Fad6b87e773bfa20e3a021a8c6beaecb2%2F3.gif?generation=1709116602003327&alt=media" alt="">

Researchers and healthcare professionals can use this dataset to study spinal conditions and disorders, such as herniated discs, spinal stenosis, scoliosis, and fractures. The dataset can also be used to develop and evaluate new imaging techniques, computer algorithms for image analysis, and artificial intelligence models for automated diagnosis.

OTHER MEDICAL SPINE MRI DATASETS:

• Spinal Cord Images - Spine MRI Dataset
• Spine Segmentation Dataset - MRI Images
• Spine MRI Dataset -Anomaly Detection
• Spine Magnetic Resonance Imaging Dataset

💴 Buy the Dataset: This is just an example of the data. Leave a request on https://trainingdata.pro/datasets to discuss your requirements, learn about the price and buy the dataset

Content

The dataset includes:

• ST000001: includes subfolders with 5 studies. Each study includes MRI-scans in .dcm and .jpg formats,
• DICOMDIR: includes information about the patient's condition and links to access files,
• Spine_MRI_4.pdf: includes medical report, provided by the radiologist,
• .csv file: includes id of the studies and the number of files

Medical reports include the following data:

• Patient's demographic information,
• Description of the case,
• Preliminary diagnosis,
• Recommendations on the further actions

All patients consented to the publication of data

Medical data might be collected in accordance with your requirements.

TrainingData provides high-quality data annotation tailored to your needs

keywords: visual, label, positive, negative, symptoms, clinically, sensory, varicella, syndrome, predictors, diagnosed, rsna cervical, image train, segmentations meta, spine train, mri spine scans, spinal imaging, radiology dataset, neuroimaging, medical imaging data, image segmentation, lumbar spine mri, thoracic spine mri, cervical spine mri, spine anatomy, spinal cord mri, orthopedic imaging, radiologist dataset, mri scan analysis, spine mri dataset, machine learning medical imaging, spinal abnormalities, image classification, neural network spine scans, mri data analysis, deep learning medical imaging, mri image processing, spine tumor detection, spine injury diagnosis, mri image segmentation, spine mri classification, artificial intelligence in radiology, spine abnormalities detection, spine pathology analysis, mri feature extraction, tomography, cloud

Brain Cancer MRI Object Detection & Segmentation Dataset

The dataset consists of .dcm files containing MRI scans of the brain of the person with a cancer. The images are labeled by the doctors and accompanied by report in PDF-format.

The dataset includes 10 studies, made from the different angles which provide a comprehensive understanding of a brain tumor structure.

MRI study angles in the dataset

https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F12421376%2F5939be1e93e8e0c9f1ff922f184f70fe%2FFrame%2079.png?generation=1707920286083259&alt=media" alt="">

💴 For Commercial Usage: Full version of the dataset includes 100,000 brain studies of people with different conditions, leave a request on TrainingData to buy the dataset

Types of diseases and conditions in the full dataset:

• Cancer
• Multiple sclerosis
• Metastatic lesion
• Arnold-Chiari malformation
• Focal gliosis of the brain
• AND MANY OTHER CONDITIONS

https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F12421376%2F0f5a27b8872e85fe23bf742593dc4843%2F2.gif?generation=1707920414940375&alt=media" alt="">

The MRI scans provide high-resolution images of the anatomical structures, allowing medical professionals to visualize the tumor, its location, size, and surrounding tissues.

The dataset holds great value for researchers and medical professionals involved in oncology, radiology, and medical imaging. It can be used for a wide range of purposes, including developing and evaluating novel imaging techniques, training and validating machine learning algorithms for automated tumor detection and segmentation, analyzing tumor response to different treatments, and studying the relationship between imaging features and clinical outcomes.

OTHER MEDICAL BRAIN MRI DATASETS:

• Brain MRI - Multiple Sclerosis Dataset
• Brain Anomaly Detection Dataset
• Normal Brain MRI Dataset
• Fazekas Detection - MRI Dataset

💴 Buy the Dataset: This is just an example of the data. Leave a request on https://trainingdata.pro/datasets to discuss your requirements, learn about the price and buy the dataset

Content

The dataset includes:

• ST000001: includes subfolders with 10 studies. Each study includes MRI-scans in .dcm and .jpg formats,
• DICOMDIR: includes information about the patient's condition and links to access files,
• Brain_MRI_1.pdf: includes medical report, provided by the radiologist,
• .csv file: includes id of the studies and the number of files

Medical reports include the following data:

• Patient's demographic information,
• Description of the case,
• Preliminary diagnosis,
• Recommendations on the further actions

All patients consented to the publication of data

Medical data might be collected in accordance with your requirements.

TrainingData provides high-quality data annotation tailored to your needs

keywords: tumors, cloud, testing, glioma, related, pytorch, directories, science, improve, directory, malignant, classify, accuracy, level, classified, cancerous, magnetic, neural, resonance, mri brain scan, brain tumor, brain cancer, oncology, neuroimaging, radiology, brain metastasis, glioblastoma, meningioma, pituitary tumor, medulloblastoma, astrocytoma, oligodendroglioma, ependymoma, neuro-oncology, brain lesion, brain metastasis detection, brain tumor classification, brain tumor segmentation, brain tumor diagnosis, brain tumor prognosis, brain tumor treatment, brain tumor surgery, brain tumor radiation therapy, brain tumor chemotherapy, brain tumor clinical trials, brain tumor research, brain tumor awareness, brain tumor support, brain tumor survivor, neurosurgery, neurologist, neuroradiology, neuro-oncologist, neuroscientist, medical imaging, cancer detection, cancer segmentation, tumor, computed tomography, head, skull, brain scan, eye sockets, sinuses, computer vision, deep learning