Automated algorithm for medical data structuring, and segmentation using artificial intelligence within secured environment for dataset creation.

ABSTRACT:

Objective

Routinely collected electronic health records using artificial intelligence (AI)-based systems bring out enormous benefits for patients, healthcare centers, and its industries. Artificial intelligence models can be used to structure a wide variety of unstructured data.

Methods

We present a semi-automatic workflow for medical dataset management, including data structuring, research extraction, AI-ground truth creation, and updates. The algorithm creates directories based on keywords in new file names.

Results

Our work focuses on organizing computed tomography (CT), magnetic resonance (MR) images, patient clinical data, and segmented annotations. In addition, an AI model is used to generate different initial labels that can be edited manually to create ground

SUBMITTER: Nainamalai V 

PROVIDER: S-EPMC11260947 | biostudies-literature | 2024 Dec

REPOSITORIES: biostudies-literature