LabAnalyzer Reviews

Machine learning can provide insightful text analysis that extracts, analyses, and stores text. AutoML allows you to create high-quality custom machine learning models without writing a single line. Natural Language API allows you to apply natural language understanding (NLU). To identify and label fields in a document, such as emails and chats, use entity analysis. Next, perform sentiment analysis to understand customer opinions and find UX and product insights. Natural Language with speech to text API extracts insights form audio. Vision API provides optical character recognition (OCR), which can be used to scan scanned documents. Translation API can understand sentiments in multiple languages. You can use custom entity extraction to identify domain-specific entities in documents. Many of these entities don't appear within standard language models. This allows you to save time and money by not having to do manual analysis. You can create your own machine learning custom models that can classify, extract and detect sentiment.

Amazon Comprehend is a HIPAA-eligible, natural language processing (NLP), service that uses machine-learning to extract health data form medical text. No machine learning experience is necessary. Today, a lot of health data is found in free-form medical texts like doctor's notes, clinical trials reports, and patient records. Manually extracting data can be time-consuming and automated rule-based attempts at extracting data won't capture the whole story because they don't take context into consideration. The data is not usable for large-scale analytics that will help improve the healthcare and life sciences industry, patient outcomes, and increase efficiencies.