Classify health-related text in colloquial language according to the presence or absence of drug side effects.
~$12,000/yr est.
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Offering: A comprehensive suite of NLP-based clinical entity recognition models and structured healthcare datasets for pharmacovigilance, clinical research, and population health analytics.
Best for: Healthcare data scientists and clinical researchers building automated pipelines for medical record de-identification and drug safety monitoring.
Get an instant price estimate based on your organization profile — seats, usage rights, and contract term.Estimated ~$12,000/yr est.
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A Large Language Models for Multi-Class and Multi-Label Detection ...
promising tool for side effect prediction in drug discovery. Viera et al ... To construct high-quality dataset for drug abuse detection and overdose symptom ...
Utilizing AI and Social Media Analytics to Discover Adverse ...
Dataset 5: Side Effects Reported by Manufacturers and by ChatGPT. We manually searched on the web to collect ASEs reported by drug manufacturers ...
A Weak Supervision Approach for Monitoring Recreational ...
We used two complementary sources of information to identify whether a tweet refers to the use or effects of recreational drugs: (1) a curated ...
Expected fields and columns in this data product
Detect Drug Side Effect Narratives is an alternative data product offered by John Snow Labs, available on databricks_marketplace. API access is available for programmatic integration. Vedex estimates pricing at roughly $12,000/yr (an estimate, not a vendor-published price).
Classify health-related text in colloquial language according to the presence or absence of drug side effects.
John Snow Labs is a data provider vendor based in Wilmington, Delaware, USA. The model is a powerful tool for extracting SDoH entities from clinical text. It was specifically trained to identify the conditions in which people are born, grow, live, work, and age that impacts th...