Data-Driven Healthcare.

End-to-End Medical Technology Solutions, Powered by AI.

Healthcare organizations in the age of data are under enormous pressure. The need to improve quality of care and patient experiences, while continually lowering healthcare delivery costs, is driving investments in smart solutions for better decision-making. CapeStart’s machine learning models and applications allow providers, payers and vendors to use data to make better decisions and improve healthcare outcomes.

Data Annotation, ML & Software Development for Healthcare.

Our integrated, in-house team of data scientists, software engineers and data annotation experts provide end-to-end machine learning and software solutions for healthcare organizations of all sizes and market segments. From data collection, to data labeling and annotation, to machine learning applications, to pre-trained models and pre-annotated third-party datasets, CapeStart’s got you covered.

  • Medical image, video and text annotation and preparation including radiography, ultrasonography, mammogramography, CT scans, MRIs and photon emission tomography
  • Natural language processing (NLP) including medical text classification, named entity recognition, text analysis, and topic modeling for pharmaceutical and other healthcare use cases
  • AI and machine learning software development for healthcare
  • Pre-trained machine learning models for healthcare

Healthcare Industry
Use Cases.

CapeStart helps organizations across the healthcare spectrum harness the power of data through AI to improve operations, lower costs, and deliver the best care possible.


Uncover insights and boost drug discovery, drug repurposing, and drug targeting efforts with natural language processing (NLP) and deep learning of structured and unstructured text. Discover insights from millions of pages of anonymized electronic health records, clinical studies, trials, patient forums, social media data and other sources.


Offering and Expertise: Expert Labeling, ProNotate platform, Software Services, HIPAA Compliance, Prebuilt Models, Datasets, ongoing Human-in-the-Loop services


Leverage machine learning and predictive modeling to reduce clinical trial costs, gain valuable insights, and improve drug targeting, identification and design. Biotech companies can use AI to analyze big datasets, manage clinical trial datasets, and even perform virtual screening of billions of molecules using machine learning algorithms.


Offering and Expertise: Expert Labeling Services, ProNotate platform, Machine Learning Development Services, Prebuilt Models, Datasets, Audit and testing services

Medical Device Vendors.

Vendors of medical devices, instruments and medical IoT products can use AI to fine-tune sales and marketing efforts, boost renewals, improve the effectiveness of sales teams, create more effective messaging based on data analysis, and create better products through insights derived from machine learning.


Offering and Expertise: ProNotate for Labeling, Software Engineering, Labeling Services, Prebuilt Models, Datasets, ongoing Human-in-the-Loop services


Allocate resources such as ICU beds and manage inpatient and outpatient care more effectively through machine learning. Hospitals can use a combination of local demographic data, historical patient data, health event data and even environmental factors to build machine learning models that can predict patient inflows by the day or even by the hour, improve staffing efficiency, and even manage inventory more effectively than ever before.


Offering and Expertise: Machine Learning Software Engineering, Labeling Services, ProNotate for Labeling, Prebuilt Models, Datasets


Pharmacies dealing directly with the public can use AI to forecast pharma inventories more effectively, along with sales and staffing projections to optimize operations, save money and provide better service. Pharmacies can also use machine learning to drive more effective referral programs and run better, more targeted marketing campaigns.


Offering and Expertise: ProNotate for Labeling, Machine Learning Software Engineering, Prebuilt Models, Datasets, ongoing Human-in-the-Loop services


Payers can use big datasets, machine learning and big data analytics to identify high-risk insurance plan members (both in terms of plan renewals and risk of readmission), discover health insurance fraud faster, and build predictive models to forecast future cost of care, estimate the potential frequency of large claims, and improve risk adjustment factor (RAF) analysis.


Offering and Expertise: Expert Labeling Services, ProNotate platform, Machine Learning Development Services, Prebuilt Models, Datasets, Audit and testing services

Software & IT.

AI and big data analytics can help healthcare IT teams facing unprecedented challenges including ever-increasing volumes and velocities of data, personally identifiable information (PII) and personal health information (PHI) identification and classification within sprawling data warehouses, cybersecurity, HIPAA compliance and cost efficiency.


Offering and Expertise: Software Development Services, HIPAA Compliance, Data Security, Cloud Migration, Infrastructure Setup, Analytical Dashboards, Devops, Quality Audit and Testing services


The inability to accurately predict and allocate healthcare staffing often leads to overwork, burnout, and even increased risk of malpractice. Machine learning models and applications help healthcare providers optimize staffing levels When correctly built and trained with high-quality data, these models can predict the number of patients likely to be admitted in a given time period (one to six weeks) so the hospital can plan staffing accordingly.


Offering and Expertise: Machine Learning Development Services, Prebuilt Models, Datasets, Expert Labeling Services, ProNotate platform

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