Gavin Lillywhite explains why it's time to stop talking and start acting to improve data quality and accessibility.

AI and ML projects will fail without good data because data is the foundation that enables these technologies to learn. Data ...

Island Health says it’s “not able to constantly upload data to inform a ‘real time’ prediction,” uploading the data “once per ...

Google popularized the term "knowledge graph" in this 2012 blog post. Since then, there has been a massive momentum around ...

Tucked in the Trump administration’s sweeping AI action plan announced Wednesday is a recommendation that tech companies with ...

Microsoft is investing in European language technology with new AI initiatives focusing on multilingual models, open-source ...

South African companies looking to take advantage of the potential of large language models need to understand the crucial ...

AI models learn by identifying patterns and relationships within the data they are trained on. If this data is riddled with errors, inconsistencies, missing values, or biases, the AI will internalize ...

Proper handling of continuous variables is crucial in healthcare research, for example, within regression modelling for descriptive, explanatory, or predictive purposes. However, inadequate methods ...

Unstructured clinical data (which doesn’t conform to structured fields like drop-downs or checkboxes) includes clinical notes ...

Any implementation of AI requires access to significant amounts of data and is not without its risks as carriers and brokers ...

When ChatGPT and similar generative AI products craft responses, they can only rely on training data up to a point. Muck Rack ...