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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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We Scale Teams for:
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.
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
Image Segmentation
Image Classification
Data Entry
Named Entity Recognition (NER)
Refining object boundaries through polygonal annotation enhances your model understanding.
Precise delineation of areas of interest within medical images ensures accurate training data for your diagnostic algorithms.
By categorizing medical images into relevant classes, our annotators help optimize your algorithms for effective sorting and identification.
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.
Identification and classification of key entities within textual data (e.g., medical records) enables structured information retrieval.
Polygonal Annotation
Refining object boundaries through polygonal annotation enhances your model understanding.
Image Segmentation
Precise delineation of areas of interest within medical images ensures accurate training data for your diagnostic algorithms.
Image Classification
By categorizing medical images into relevant classes, our annotators help optimize your algorithms for effective sorting and identification.
Data Entry
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.
Named Entity Recognition (NER)
Identification and classification of key entities within textual data (e.g., medical records) enables structured information retrieval.
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
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
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.
Our Success Stories
Main challenge:
Using the client’s labeling system and handling varying and vast data flow.
Solution:
Flexible team able to perform image classification within the client’s tooling.
Scalable Medical Data Annotation for BioTech
Label Your Data partnered with a US-based biotech company for a 7-month project involving the annotation of 100,000 blood cell images daily. The task required identifying a single faulty cell among 10 in each image. The team had to adapt to the client’s annotation system, maintaining communication efficiency, and ensuring accurate results. For this, we assembled an adaptable team of 5 members, while scaling up as needed. As a result, an impressive 98% accuracy was achieved.
Main challenge:
Accurately annotating diverse wound images for AI training.
Solution:
On-demand team that skillfully delivers image categorization and segmentation.
Data Annotation for Wound Assessment Software
For a US-based AI wound assessment software company, we’ve formed an on-demand team to label and categorize wound images by severity and type. Our approach also involved segmentation techniques to optimize the algorithm’s wound detection accuracy. Our annotation tooling allows the Client to provide direct feedback on images and labels, fostering seamless collaboration for process enhancement.
Main challenge:
Assembling an expert team while ensuring a secure and scalable workflow.
Solution:
Recruiting medically skilled team, training for secure OCR annotation and text classification.
Secure Medical Records Annotation for Law Firm
A legal services company asked us to securely annotate 50,000+ medical records over 3 months. This entailed OCR annotation, text classification, and a 20-member team. Upholding data security during transfer and ensuring precise diagnosis were key. Despite scalability concerns, we swiftly established the team with medical background in 4 weeks, offering thorough training. Through a secure office setup, frequent sync meetings, and a robust 90%+ manual QA aided by automated tests, the project delivered meticulous results.
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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.
Kyle Hamilton
PhD Researcher at TU Dublin
Trusted by ML Professionals
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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.