The new federated AI blueprint from T-RIZE and Flower enhances data privacy, compliance, and auditability for enterprise ...

In terms of diagnostic accuracy, ChatGPT's performance was evaluated based on its ability to correctly identify whether a ...

JFrog deserves its premium valuation due to its critical role in the software supply chain and negligible competition. Learn ...

The 10 hottest data science and machine learning tools include MLflow 3.0, PyTorch, Snowflake Data Science Agent and ...

Patient characteristics and model fairness across subgroups. Credit: JAMA Network Open (2025). DOI: 10.1001/jamanetworkopen.2025.13685 ...

A machine learning model may be reliable for determining risk for postpartum depression, underscoring the need for greater mental health screening in those who have recently given birth, according ...

Data collected by AI-driven systems may be vulnerable to software privacy concerns or model tampering, as they rely on infrastructure for data storage, encryption, and access. 86 Meanwhile, a major ...

Machine learning model helps identify patients at risk of postpartum depression. ScienceDaily . Retrieved June 11, 2025 from www.sciencedaily.com / releases / 2025 / 05 / 250519131029.htm ...

Light-based data made clearer with new machine learning method. ScienceDaily . Retrieved June 11, 2025 from www.sciencedaily.com / releases / 2025 / 04 / 250428220611.htm ...

This study aimed to predict tumor response to nivolumab anti–PD-1 antibody treatment for advanced RCC by integrating genetic and clinical data using machine learning (ML). Methods Clinical and ...

A machine learning framework that uses scarce and sparse experimental data to both predict and inversely design the mechanical behavior of spinodal metamaterials. Why It Matters The method enables ...

It can be relatively cheap to gather a lot of bio-signal data. To teach a machine-learning algorithm to find a relationship between bio-signals and health outcomes, however, you need to teach the ...