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TU Dublin Quotes

Label Your Data were genuinely interested in the success of my project, asked good questions, and were flexible in working in my proprietary software environment.

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TU Dublin
Kyle Hamilton

Kyle Hamilton

PhD Researcher at TU Dublin

Trusted by ML Professionals

Trusted by ML Professionals

Data Annotation Services for Next-Level Healthcare

Explore new frontiers of AI in healthcare with our data annotation in medical industry. From medical lexicon to vast medical records, we’ve got you covered!

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Healthcare

We Scale Teams for:

ABB – ASEA Brown Boveri
Uipath
Yale
Bizerba
George Washington University
Toptal
Miami University
Hypatos
NEX
ABB – ASEA Brown Boveri
Uipath
Yale
Bizerba
George Washington University
Toptal
Miami University
Hypatos
NEX
ABB – ASEA Brown Boveri
Uipath
Yale
Bizerba
George Washington University
Toptal
Miami University
Hypatos
NEX

Data Annotation for Healthcare Industry at Label Your Data

Given the intricacy of this domain, data annotation for healthcare demands exceptional precision and security. Our experts meet these requirements, fortified by years of industry experience and security certifications, such as PCI DSS (level 1) and ISO:27001. We offer comprehensive medical data labeling of X-rays, MRIs, and CT scans, as well as clinical records and biomedical data.

These medical annotations fuel AI-driven applications like disease detection, treatment personalization, and drug development. On request, we can hire a medical expert to join a project along with our clinical annotation specialists. This will ensure that annotations align with medical nuances, vital for advancing diagnostics, treatments, and innovations, while upholding patient privacy measures.

svg On photo: Olha, Karyna

Our Medical Data Annotation for Healthcare Companies

For our clients from healthcare, we ensure that training healthcare datasets we provide for your machine learning applications is accurate and reliable. We have expertise in handling different formats under our belt, such as MRI scans, images, medical records, and chats with patients.

Through our data annotation for the healthcare industry, we empower medical AI to make accurate diagnoses, propose effective treatments, and drive advancements in patient care. We specialize in diverse types of medical data annotation (this is not an exhaustive list of services we offer for medical data annotation):

Polygonal Annotation

Polygonal Annotation

Image Segmentation

Image Segmentation

Image Classification

Image Classification

Data Entry

Data Entry

Named Entity Recognition (NER)

Named Entity Recognition (NER)

Refining object boundaries through polygonal annotation enhances your model understanding.

Refining object boundaries through polygonal annotation enhances your model understanding.

Get Polygonal Annotation
Precise delineation of areas of interest within medical images ensures accurate training data for your diagnostic algorithms.

Precise delineation of areas of interest within medical images ensures accurate training data for your diagnostic algorithms.

Get Image Segmentation
By categorizing medical images into relevant classes, our annotators help optimize your algorithms for effective sorting and identification.

By categorizing medical images into relevant classes, our annotators help optimize your algorithms for effective sorting and identification.

Get Image Classification
In addition to data labeling for healthcare, we provide a range of additional services. Seamless translation of manual medical records into digital formats enriches your healthcare dataset for comprehensive ML model training.

In addition to data labeling for healthcare, we provide a range of additional services. Seamless translation of manual medical records into digital formats enriches your healthcare dataset for comprehensive ML model training.

Get Data Entry
Identification and classification of key entities within textual data (e.g., medical records) enables structured information retrieval.

Identification and classification of key entities within textual data (e.g., medical records) enables structured information retrieval.

Get Named Entity Recognition
Polygonal Annotation

Polygonal Annotation

svg
Refining object boundaries through polygonal annotation enhances your model understanding.

Refining object boundaries through polygonal annotation enhances your model understanding.

Get Polygonal Annotation
Image Segmentation

Image Segmentation

svg
Precise delineation of areas of interest within medical images ensures accurate training data for your diagnostic algorithms.

Precise delineation of areas of interest within medical images ensures accurate training data for your diagnostic algorithms.

Get Image Segmentation
Image Classification

Image Classification

svg
By categorizing medical images into relevant classes, our annotators help optimize your algorithms for effective sorting and identification.

By categorizing medical images into relevant classes, our annotators help optimize your algorithms for effective sorting and identification.

Get Image Classification
Data Entry

Data Entry

svg
In addition to data labeling for healthcare, we provide a range of additional services. Seamless translation of manual medical records into digital formats enriches your healthcare dataset for comprehensive ML model training.

In addition to data labeling for healthcare, we provide a range of additional services. Seamless translation of manual medical records into digital formats enriches your healthcare dataset for comprehensive ML model training.

Get Data Entry
Named Entity Recognition (NER)

Named Entity Recognition (NER)

svg
Identification and classification of key entities within textual data (e.g., medical records) enables structured information retrieval.

Identification and classification of key entities within textual data (e.g., medical records) enables structured information retrieval.

Get Named Entity Recognition
Patient Data Privacy

Patient Data Privacy

Given the highly sensitive nature of healthcare data, often containing personal patient information, we prioritize data security. To maintain the highest standards, all our processes undergo meticulous annual audits to ensure compliance with both HIPAA and ISO:27001 certifications.

Medical Annotation Expertise

Medical Annotation Expertise

Additionally, our expertise sets us apart. We’ve successfully undertaken diverse healthcare projects, including NER for medical reports, image annotation for burns and skin conditions, MRI scan labeling, and colonoscopy tube image labeling, among others.

Subject-Matter Specialists

Subject-Matter Specialists

Our data annotation in healthcare services stand out for scalability in recruiting medical experts for a project. When clients require doctors, radiologists, or pharmacists on the team, our robust HR reputation and global annotation hubs enable swift and precise specialist delivery.

Why Choose Data Annotation in Healthcare at Label Your Data?

Our company holds certifications for PCI DSS (level 1) and ISO:27001, and we adhere to the regulations outlined by GDPR, CCPA, and HIPAA. With 10+ years of experience and 500+ specialists on board, we provide customized data annotation services for healthcare for enterprise and R&D projects in 55 languages.

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FAQs

What does a medical annotator do in the context of data annotation for the healthcare industry?

A medical annotator labels medical images, records, or other data, identifying and highlighting specific medical entities, conditions, or features as part of data annotation for the healthcare industry.

How does data annotation in the medical industry enhance AI-based diagnostic tools and treatment suggestions?

Data annotation for healthcare plays a crucial role in advancing AI-powered solutions in this industry. Thanks to well-annotated training data, machine learning models are able to learn and identify intricate patterns for precise disease diagnosis and personalized treatment guidance.

What is medical text annotation?

Text data annotation in healthcare involves labeling specific information, such as medical conditions, treatments, and symptoms, within medical texts to create labeled datasets used for training NLP models in the healthcare domain.

What are the common types of data annotation in medical imaging?

The typical types of data labeling for medical imaging include image segmentation, image classification, polygonal annotation, as well as bounding box annotation.