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Description
Utilize natural language processing to derive insights from unstructured text without needing machine learning expertise, leveraging a suite of features from Cognitive Service for Language. Enhance your comprehension of customer sentiments through sentiment analysis and pinpoint significant phrases and entities, including individuals, locations, and organizations, to identify prevalent themes and trends. Categorize medical terminology with specialized, pretrained models tailored for specific domains. Assess text in numerous languages and uncover vital concepts within the content, such as key phrases and named entities encompassing people, events, and organizations. Investigate customer feedback regarding your brand while analyzing sentiments related to particular subjects through opinion mining. Moreover, extract valuable insights from unstructured clinical documents like doctors' notes, electronic health records, and patient intake forms by employing text analytics designed for healthcare applications, ultimately improving patient care and decision-making processes.
Description
Numerous healthcare facilities, including hospitals and ambulatory surgery centers (ASCs), face considerable challenges in documenting procedures effectively. The diverse methods used by physicians for documentation—such as dictation, transcription, and electronic medical records (EMRs)—often lack uniformity, resulting in procedure notes that may be inaccurate, incomplete, or fail to meet compliance standards. Consequently, these reports tend to be unsearchable and difficult to analyze due to their reliance on unstructured data. Furthermore, inefficient workflows contribute to financial setbacks and increased frustration among physicians. To address these issues, a solution is proposed that guides physicians through an intuitive workflow navigation tree, which facilitates quick documentation by providing appropriate options. This system also aids organizations in achieving quality and compliance benchmarks by enabling users to generate over 100 reports and analyze structured data effectively. Additionally, it connects seamlessly with endoscopy scopes, allowing for the collection of relevant images that can be incorporated into procedure notes, ultimately enhancing the overall documentation process. This integrated approach not only streamlines documentation but also improves patient care by ensuring thorough and accurate records.
API Access
Has API
API Access
Has API
Integrations
Azure Marketplace
TAS Insight Engine
Unremot
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
No price information available.
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
Microsoft
Founded
1975
Country
United States
Website
azure.microsoft.com/en-us/services/cognitive-services/text-analytics/
Vendor Details
Company Name
Provation Medical
Founded
1994
Country
United States
Website
www.provationmedical.com
Product Features
Natural Language Processing
Co-Reference Resolution
In-Database Text Analytics
Named Entity Recognition
Natural Language Generation (NLG)
Open Source Integrations
Parsing
Part-of-Speech Tagging
Sentence Segmentation
Stemming/Lemmatization
Tokenization
Product Features
Patient Case Management
Activity Tracking
Assessment Notes
Billing & Invoicing
Calendar Management
Candidate Identification
Case List Management
Eligibility Verification
HIPAA Compliant
Medical History Records
Patient Records
Referral Management
Treatment Planning