In addition to making web page, human-readable forms of ontologies, pyLODE encourages ontology annotation best practice by only producing good results for well documented inputs! pyLODE defines what ...

Passive sensing via wearable devices and smartphones, combined with machine learning (ML), enables objective, continuous, and noninvasive mental health monitoring. Objective: This study aimed to ...

No system was recommended for individual prognostication, and the group considered that more detail in ulcer characterization was needed and that machine learning (ML)–based models may be the solution ...

OntoLearner is a modular and extensible Python library for ontology learning powered by Large Language Models (LLMs). It provides a unified framework covering the full workflow — from loading and ...

Copyright: © 2025 The Author(s). Published by Elsevier Ltd. Machine learning for health data science, fuelled by proliferation of data and reduced computational ...

In some ways, Java was the key language for machine learning and AI before Python stole its crown. Important pieces of the data science ecosystem, like Apache Spark, started out in the Java universe.

If you’re learning machine learning with Python, chances are you’ll come across Scikit-learn. Often described as “Machine Learning in Python,” Scikit-learn is one of the most widely used open-source ...

Postpartum depression (PPD) is a common and serious mental health complication after childbirth, with potential negative consequences for both the mother and her infant. This study aimed to develop an ...

The Department of Justice recently issued guidance encouraging federal agencies to use “artificial intelligence and machine translation to communicate with individuals who are limited English ...

When you install Python packages into a given instance of Python, the default behavior is for the package’s files to be copied into the target installation. But sometimes you don’t want to copy the ...

Recent developments in machine learning techniques have been supported by the continuous increase in availability of high-performance computational resources and data. While large volumes of data are ...