- What We Do
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Collect, De-identify, & Annotate large datasets by domain experts in Healthcare
Empowering teams to build world-leading AI products.
80% of all healthcare data is unstructured and inaccessible for further processing. This limits the quantity of usable data and also limits a healthcare organization’s decision-making capabilities. Unless you turn to Shaip.
We have a deep understanding of healthcare terminologies to unlock its potential as a result of years of experience in data transcription, de-identification, and annotation. Add to this we can also deliver the exact healthcare data you need to improve your AI engine.
Industry:
According to a study, 30% of healthcare costs are associated with administrative tasks. AI can automate some of these tasks, like pre-authorizing insurance, following-up on unpaid bills, & maintaining records, to ease the workload.
Industry:
As per recent research machine-learning algorithms can analyze 3D scans up to 1000 times faster than what is possible today. It can offer real-time assessment and critical inputs to a surgeon to make a more informed decision.
The global healthcare AI market size is expected to grow from USD 3.64 billion in 2019 to USD 33.42 billion by 2026, at a Compound Annual Growth Rate (CAGR) of 46.21% during the forecast period.
Then we give it structure, and purpose through natural language processing (NLP) that delivers domain-specific insights on symptoms, diseases, allergies, and medications. Now the healthcare community, through Shaip AI data, has the right insights to make better decisions that result in better patient outcomes.
AI-enabled companies turn to us to create training data sets so that they can develop cutting-edge machine learning algorithms for the healthcare industry. View our full healthcare catalog.
From advancing care to providing healthcare organizations with a solution to control costs while improving patient outcomes, the right data can power AI and ML to achieve these goals through Shaip. After all, better data means better outcomes.
Readily Available Datasets: View Full Catalog
Our PHI/PII deidentification capabilities include removal of sensitive information such as names and social security numbers that may directly or indirectly connect an individual to their personal data. Its what patients deserve and HIPAA demands.
Our proprietary de-identification platform can anonymize sensitive data in text content with extremely high accuracy. APIs extract the PHI/PII entities present in text or image datasets and then mask, delete, or obscure those fields to provide de-identified data
Shaip annotation services can add the much-needed power to boost your AI engine. X-Ray, CT scans, MRI, and other image-based test reports can be easily screened to predict various ailments. We can help you annotate complex healthcare records i.e. text or images to develop your AI ML models.
We can scale to 1000s of people to manage any size project. The outcome? Faster healthcare image annotation to build your models within your timeframe and budget.
When you need data in real-time you should be able to access APIs just as quickly. This is why Shaip APIs provide real time, on-demand access to the records you need. With Shaip APIs your teams now have fast and scalable access to de-identified records and quality contextualized medical data to complete their AI projects right the first time.
Data that powers brings Medical AI to life
Shaip provided high-quality data
for AI models in healthcare to improve
patient care. Delivered 30,000+
de-identified clinical documents adhering
to Safe Harbor Guidelines. These clinical
documents were annotated with 9 clinical
entity
De-identify and annotate clinical documents from domain experts
De-Identified & annotated 30,000+ documents per client guideline
Gold Standard clinical data to develop client’s NLP and Healthcare
Scale data de-identification across different regulatory jurisdictions including GDPR, HIPAA, and as per Safe Harbor, De-identification that reduces risks of compromise of PII/PHI
The market value of artificial intelligence in healthcare hit a new high in 2020 at $6.7bn. Experts in the field and tech veterans also reveal that the industry would be valued at around $8.6bn by the year 2025.
Data procurement has always been an organizational priority. More so when the concerned data sets are used to train autonomous, self-learning setups.
Our medical data catalog datasets are not only massive but have gold-standard quality data. Rest assured that the data you utilize is secure, de-identified.
Tell us how we can help with your next AI initiative.
AI in healthcare involves using artificial intelligence technologies to assist in diagnosis, treatment, and patient management.
AI is utilized for disease diagnosis from medical images, personalized treatment recommendations, speeding up drug research, managing medical records, predictive analytics, assisting in surgeries, and offering virtual health assistance.
AI enhances accuracy in diagnosis, boosts efficiency, saves costs, enables personalized treatments, provides predictive insights, and increases healthcare accessibility.
Applications include medical imaging analysis, genomic research, drug discovery, optimizing treatments, remote health monitoring, chatbots for patient queries, and improving hospital operations.
AI manages vast medical data, facilitates early disease detection, optimizes resource allocation, reduces errors, accelerates research, and improves the patient experience.