Known adverse reactions
References to PubMed citations
Common and scientific names
All known uses
Evidence-based safety ratings
Evidence-based effectiveness ratings
Mechanism of action
Building the #1 natural-care dataset
Unali aims to build the first open-access, ontology-based database for Traditional, Complementary and Alternative Medicine (TCAM) products. The database includes:
Generating high-quality, ethically sourced data sets is crucial for enabling the use of next-generation AI technologies.
The foundation of our dataset is a relational representation of products in terms of characteristics and applications. We build it using keyword extraction and the use of triplet networks to derive semantically meaningful representations of text.
The Unali user experience is designed to collect behavioral data. We use this data to build user cohorts to optimize our recommendations and gain insights into people’s interests and needs in the context of Traditional, Complementary and Alternative care.
We provide users with fine-grained surveys to collect data on users' attitude towards natural care, their expectations before and satisfaction after treatments. Such data allows us to carry out comparisons with conventional medicine.
We integrate in our portal access to several million publications as recommended reads. We use a mixture of keyword and AI-built representations to categorize papers by keywords and link them to specific products.
Data is a cornerstone for efforts to address disparities and advance health equity. Availability of high-quality, comprehensive data disaggregated by race/ethnicity is a prerequisite consideration included in building this dataset.
Our data pipeline ingests products, behavioral, qualitative and clinical data. The output is the first ever ontology-based TCAM database. It is designed to enable you to formulate and answer quantitative questions to monitor the performance of treatments, related products and more.