Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
HIN+AI represents a mobile-centric, advanced #HealthIT solution designed around a blockchain-based electronic health record system, featuring an XDS-compatible clinical content manager, cloud-based multi-tenant patient administration system, and practice management tools with customizable data querying and analytical functions. The initial version of HIN+AI incorporates clinical decision support tools, intelligent notifications, a scheduling system with an integrated Computerized Physician Order Entry (CPOE), and a results viewer, making it a robust electronic medicine environment that securely stores your personal data on smartphones, tablets, or PCs. At its core, deep learning focuses on recognizing patterns through interconnected data points, and HIN+AI leverages these techniques to convert vast EHR datasets into meaningful knowledge and practical insights. Furthermore, the blockchain functionality of HIN+AI ensures the interoperability, integrity, and security of health data, allowing users to own and manage their data through cryptographically secured and immutable exchange systems. Additionally, it can aggregate and analyze information from various wearable health devices and sensors, enhancing the overall health management experience. This integration not only streamlines data processing but also offers comprehensive insights into individual health trends.
Description
We have been pioneers in the development of clinical NLP platforms and their applications for over 15 years. This has resulted in high precision and accuracy. Our core competency is to interpret unstructured notes accurately and at scale. Tested on billions of real clinical notes and documents. AI that can explain with context, reasoning, and evidence for output. NLP with medical knowledge infused with 4M+ entities and 50M+ relationships. Innovative Machine Learning (ML), & Deep Learning(DL) models were used to build this NLP. Use a foundation of rich ontologies and clinician-specific terminologies. We can understand, interpret, and extract context & significance from the inconsistent, inconsistent, and non-standard data contained in medical documents. Our clinical domain experts continually infuse knowledge graphs to our NLP by mapping all clinical entities and their relationship between them. We have more than 4,000,000 entities and 50,000,000 relationships.
API Access
Has API
No
API Access
Has API
Yes
Integrations
No details available.
Integrations
No details available.
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)
Yes
Online Support
Yes
Customer Support
Business Hours
Yes
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
Yes
In Person
Yes
Types of Training
Training Docs
Yes
Webinars
Yes
Live Training (Online)
Yes
In Person
Yes
Vendor Details
Company Name
ICT Health Technology Services India
Founded
2010
Country
United Arab Emirates
Website
www.icthealth.com
Vendor Details
Company Name
RAAPID INC
Founded
2022
Country
United States
Website
www.raapidinc.com
Product Features
Hospital Management
Accounting Integration
Yes
Appointment Management
Yes
Appointment Scheduling
Yes
Bed Management
Yes
Billing & Invoicing
Yes
Claims Management
Yes
In-Patient Management
Yes
Inventory Management
Yes
Medical Billing
Yes
Out-Patient Management
Yes
Patient Records Management
Yes
Physician Management
Yes
Policy Management
Yes
Revenue Management
Yes
Product Features
Natural Language Processing
Co-Reference Resolution
No
In-Database Text Analytics
No
Named Entity Recognition
No
Natural Language Generation (NLG)
No
Open Source Integrations
No
Parsing
No
Part-of-Speech Tagging
No
Sentence Segmentation
No
Stemming/Lemmatization
No
Tokenization
No