article thumbnail

Now in Public Preview: Processing Files and Unstructured Data with Snowpark for Python

Snowflake

“California Air Resources Board has been exploring processing atmospheric data delivered from four different remote locations via instruments that produce netCDF files. Previously, working with these large and complex files would require a unique set of tools, creating data silos. ” U.S.

article thumbnail

Medical Datasets for Machine Learning: Aims, Types and Common Use Cases

AltexSoft

Everyday the global healthcare system generates tons of medical data that — at least, theoretically — could be used for machine learning purposes. Regardless of industry, data is considered a valuable resource that helps companies outperform their rivals, and healthcare is not an exception. Medical data labeling.

Medical 52
Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

Natural Language Processing in Healthcare: Using Text Analysis for Medical Documentation and Decision-Making

AltexSoft

This allows machines to extract value even from unstructured data. Healthcare organizations generate a lot of text data. But a lot of data (by different estimations, 70 or 80 percent of all clinical data) remains unstructured , kept in textual reports, clinical notes, observations, and other narrative text.

Medical 52
article thumbnail

Processing medical images at scale on the cloud

Tweag

To allow innovation in medical imaging with AI, we need efficient and affordable ways to store and process these WSIs at scale. Most training pipelines and systems are designed to handle fairly small, sub-megapixel images. An issue is open to handle this case, but it made us decide not to use it.

Medical 60
article thumbnail

4 Ways Better Access to Healthcare Data Can Improve Patient Outcomes

Snowflake

But all of this important data is often siloed and inaccessible or in hard-to-process formats, such as DICOM imaging, clinical notes or genomic sequencing. Healthcare organizations must ensure they have a data infrastructure that enables them to collect and analyze large amounts of structured and unstructured data at the point of care.

article thumbnail

Importance of Data Science in 2024 [A Simple Guide]

Knowledge Hut

In the twenty-first century, data science is regarded as a profitable career. It is simply the study of mathematics, statistics, and computer science to extract information from structured and unstructured data. Data science, which solves problems by connecting relevant data for later use, aids these emerging technologies.

article thumbnail

Claims Processing with Generative AI: Making Sense of the Data

Precisely

From documenting losses and damages to verifying that a claim submission meets all the necessary criteria, each step requires meticulous attention to detail and often entails reviewing lengthy narrative documents such as accident reports, medical records, and legal demands letters.