Free Trial
The Clinical De-Identification model is designed to recognize and anonymize PHI in Spanish-language clinical notes. It employs state-of-the-art natural language processing techniques to detect sensitive information such as patient names, addresses, medical record numbers, and other identifiers....
Model Package - Fulfilled on Amazon SageMaker
Free Trial
This model is specialized in health-related text analysis in colloquial language within the domain of Public Health and Voice of Patients. It is designed to identify and extract various entities such as Diagnosis, Treatments, Tests, Psychological Conditions, Relationship Status, Symptoms,...
Model Package - Fulfilled on Amazon SageMaker
Free Trial
This SageMaker model package provides a REST api to detect named entities in US English sentences. The API accepts input as JSON and identifies entities in an input text array. We welcome your feedback at aws-support@sigmodata.com. To see a notebook with usage instructions go to...
Model Package - Fulfilled on Amazon SageMaker
Free Trial
EXL XtraktoAI™ Medication Extraction solution focuses to extract and normalize drug data stored in free text fields of Electronic Health Record (EHR) or unstructured medical records or any document. The solution maps the extracted drugs with its respective RxCUI associated with RxNorm. It also...
Model Package - Fulfilled on Amazon SageMaker
Free Trial
The Clinical De-Identification model is designed to recognize and anonymize PHI in Italian-language clinical notes. It employs state-of-the-art natural language processing techniques to detect sensitive information such as patient names, addresses, medical record numbers, and other identifiers....
Model Package - Fulfilled on Amazon SageMaker
This is a Named Entity Recognition model built upon a Transformer model from [Hugging Face](https://huggingface.co/elastic/distilbert-base-cased-finetuned-conll03-english). It takes a text string as input and predicts named entities in the input text. The deployed model can be used for running...
Model Package - Fulfilled on Amazon SageMaker
Free Trial
The Clinical De-Identification model is designed to recognize and anonymize PHI in Romanian-language clinical notes. It employs state-of-the-art natural language processing techniques to detect sensitive information such as patient names, addresses, medical record numbers, and other identifiers....
Model Package - Fulfilled on Amazon SageMaker
Free Trial
The Clinical De-Identification model is designed to recognize and anonymize PHI in Arabic-language clinical notes. It employs state-of-the-art natural language processing techniques to detect sensitive information such as patient names, addresses, medical record numbers, and other identifiers. Once...
Model Package - Fulfilled on Amazon SageMaker
Philter Managed Deployment simplifies the deployment of Philter to find and remove sensitive information from text. An AWS certified professional engineer will provision a HIPAA-compliant architecture leveraging encryption of all data at rest and in motion containing a highly-available and scalable...
Free Trial
Identify socio-environmental health determinants like access to care, diet, employment, and housing from health records. Tailored for professionals and researchers, this pipeline extracts key factors influencing health in social, economic, and environmental contexts.
Model Package - Fulfilled on Amazon SageMaker
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