Deep-Transfer-Learning–Based Natural Language Processing of Serial Free-Text Computed Tomography Reports for Predicting Survival of Patients With Pancreatic Cancer The first approach led to a ...

Leveraging Centralized Health System Data Management and Large Language Model–Based Data Preprocessing to Identify Predictors for Radiation Therapy Interruption This study presents a new method based ...

A multidisciplinary team at UT Southwestern Medical Center has developed an AI-enabled pipeline that can quickly and accurately extract relevant information from complex, free-text medical records.

Modern consumer-facing organizations rely on collaborative, data-driven decisions to fuel their business—yet the challenge is to do so with a keen focus on ensuring sound, well-maintained, accessible ...

Information is the new oil, and fast data extraction sets leaders apart. As web data grows rapidly, practical tools are needed to extract this information. Traditional web scraping methods often ...

For years, businesses, governments, and researchers have struggled with a persistent problem: How to extract usable data from Portable Document Format (PDF) files. These digital documents serve as ...

Have you ever stared at a massive spreadsheet, overwhelmed by the chaos of mixed data—names, IDs, codes—all crammed into single cells? It’s a common frustration for anyone managing large datasets in ...

Recently, AI researcher Simon Willison wanted to add up his charges from using a cloud service, but the payment values and dates he needed were scattered among a dozen separate emails. Inputting them ...

To get data on the injuries, Cedars-Sinai is using AI to extract data from chart notes. At HIMSS25, Kathy Bailey, principal data intelligence analyst for Cedars-Sinai, will explain what she and her ...