At Lelapa AI, we're committed to advancing language technology and broadening its reach with our specialized Vulavula Multilingual Named Entity Recognition (NER) Model, particularly designed for Africa's linguistic diversity. This innovative model efficiently identifies and categorizes named...
Model Package - Fulfilled on Amazon SageMaker
This solution creates a knowledge graph based on entity-name pairs from data collected from multiple sources of information such as Wikipedia, company's website, CrunchBase etc. This solution creates a graph model of a company's profile based on unstructured data.
Model Package - Fulfilled on Amazon SageMaker
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This model is engineered for radiology texts and reports, adeptly identifying entities such as imaging tests, imaging techniques, imaging findings, and more. It also automatically detects the assertion status of the findings: Confirmed, Suspected, Negative, and can find relations between diagnosis,...
Model Package - Fulfilled on Amazon SageMaker
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This model extracts biological and genetics entities from medical texts to enhance therapeutic research, early diagnosis, and personalized care, driving forward data-driven medical advancements. The model was tailored to identify and extract various biological entities such as genes, anatomical...
Model Package - Fulfilled on Amazon SageMaker
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This model was created to facilitate the accurate mapping of drugs to their corresponding RxNorm codes and related drug classes. It is an essential tool for healthcare professionals and pharmacists, ensuring precise medication identification and categorization, which is crucial for patient safety,...
Model Package - Fulfilled on Amazon SageMaker
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This model extracts more than 40 oncology-related entities, including therapies, tests, staging, histological type, oncogene, and radiation dose from clinical documentation, pathology, and diagnostic reports, optimizing oncology workflows and advancing personalized cancer treatments. It also...
Model Package - Fulfilled on Amazon SageMaker
With YZR's API and collaborative AI platform: - Business experts spend much less time correcting, tagging and grouping textual data manually with a NLP-powered solution - Data and IT teams integrate faster and with more confidence automated textual data quality pipelines into ETLs, data lakes,...
Legal entity ownership extraction is an NLP solution that helps identify and classify legal parent and subsidiary organization names in an unstructured text. The solution takes a text file as input. The text can be sourced from documents such as financial statements and legal documents. The...
Model Package - Fulfilled on Amazon SageMaker
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This model is specialized on 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
Mphasis DeepInsights Named Entity Recognizer is an efficient way of identifying named entities present in the corpus of text. This solution applies NLP techniques to extract the named entities which can be used for further text analytics and for providing useful insights about the text. The model...
Model Package - Fulfilled on Amazon SageMaker
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