Physics World

Physicists discuss the future of machine learning and artificial intelligence

IOP Publishing’s Machine Learning series is the world’s first open-access journal series dedicated to the application and ...

Machine learning workflow enables faster, more reliable organic crystal structure prediction

Prediction of crystal structures of organic molecules is a critical task in many industries, especially in pharmaceuticals and design of functional materials. In pharmaceuticals, crystal structures ...
ascopubs.org

Integration of a machine learning model-generated surgical risk score into the EHR and preoperative workflow.

Understanding trends of US breast cancer hospitalization, mortality and costs using the National Inpatient Sample database. This is an ASCO Meeting Abstract from the 2024 ASCO Annual Meeting I. This ...
SiliconANGLE

JFrog-Amazon SageMaker integration aims to streamline machine learning workflows

Software supply chain company JFrog Ltd. announced today a new integration with Amazon SageMaker to enable developers and data scientists to collaborate efficiently on building, training and deploying ...
Nature

Machine learning workflows beyond linear models in low-data regimes

The Nature Index 2025 Research Leaders — previously known as Annual Tables — reveal the leading institutions and countries/territories in the natural and health sciences, according to their output in ...
Linux Journal

Unlocking Data Science Potential Understanding Machine Learning and Data Analysis with JupyterLab

In recent years, JupyterLab has rapidly become the tool of choice for data scientists, machine learning (ML) practitioners, and analysts worldwide. This powerful, web-based integrated development ...
Business Wire

Telescent and MIT CSAIL Collaborate to Accelerate Machine Learning Workflows

IRVINE, Calif.--(BUSINESS WIRE)--Telescent Inc., a leading manufacturer of automated fiber patch-panels and cross-connects for networks and data centers, announces today that results of the company’s ...