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Average Ratings 0 Ratings

Total
ease
features
design
support

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Write a Review

Description

SANCARE is an innovative start-up focused on applying Machine Learning techniques to hospital data. We partner with leading experts in the field to enhance our offerings. Our platform delivers an ergonomic and user-friendly interface to Medical Information Departments, facilitating quick adoption and usability. Users benefit from comprehensive access to all documents forming the electronic patient record, ensuring a seamless experience. As an effective production tool, our solution meticulously tracks each phase of the coding procedure for external validation. By leveraging machine learning, we can create robust predictive models that analyze vast data sets while considering contextual factors—capabilities that traditional rule-based systems and semantic analysis tools fall short of providing. This enables the automation of intricate decision-making processes and the identification of subtle signals that may go unnoticed by human analysts. The machine learning engine behind SANCARE is grounded in a probabilistic framework, allowing it to learn from a significant volume of examples to accurately predict the necessary codes without any explicit guidance. Ultimately, our technology not only streamlines coding tasks but also enhances the overall efficiency of healthcare data management.

Description

SquareML is an innovative platform that eliminates the need for coding, making advanced data analytics and predictive modeling accessible to a wider audience, especially within the healthcare field. It empowers users with varying levels of technical ability to utilize machine learning tools without requiring in-depth programming skills. This platform excels in aggregating data from a range of sources, such as electronic health records, claims databases, medical devices, and health information exchanges. Among its standout features are a user-friendly data science lifecycle, generative AI models tailored for healthcare needs, the ability to convert unstructured data, a variety of machine learning models to forecast patient outcomes and disease advancement, and a collection of pre-existing models and algorithms. Additionally, it facilitates smooth integration with multiple healthcare data sources. By providing AI-driven insights, SquareML aims to simplify data workflows, elevate diagnostic precision, and ultimately enhance patient care outcomes, thereby fostering a healthier future for all.

API Access

Has API No 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

Amazon Web Services (AWS) No 
Google Cloud Platform No 
Microsoft for Startups Founders Hub No 
NVIDIA DRIVE No 

Integrations

Amazon Web Services (AWS) Yes 
Google Cloud Platform Yes 
Microsoft for Startups Founders Hub Yes 
NVIDIA DRIVE Yes 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

Business Hours Yes 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs No 
Webinars No 
Live Training (Online) Yes 
In Person No 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) Yes 
In Person Yes 

Vendor Details

Company Name

SANCARE

Country

France

Website

www.sancare.fr/

Vendor Details

Company Name

SquareML

Founded

2021

Country

United States

Website

www.squareml.ai/product

Product Features

Machine Learning

Deep Learning No 
ML Algorithm Library No 
Model Training No 
Natural Language Processing (NLP) No 
Predictive Modeling No 
Statistical / Mathematical Tools No 
Templates No 
Visualization No 

Product Features

Machine Learning

Deep Learning No 
ML Algorithm Library No 
Model Training No 
Natural Language Processing (NLP) No 
Predictive Modeling No 
Statistical / Mathematical Tools No 
Templates No 
Visualization No 

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