Cloud Native

Mount Sinai’s ‘AEquity’ AI Tool Aims to Eliminate Healthcare Algorithm Bias Researchers at the Icahn School of Medicine at Mount Sinai have introduced AEquity, a novel AI tool designed to detect and mitigate biases in healthcare machine learning algorithms. As detailed in the Journal of Medical Internet Research, this tool confronts the critical challenge of algorithmic bias, which can compromise the accuracy of medical diagnoses and treatment strategies. AEquity was validated on diverse health datasets, including medical imagery and patient records, successfully identifying both known and previously undiscovered biases. The primary objective of AEquity is to ensure AI-driven healthcare solutions are both effective and equitable for all patient demographics, particularly those underrepresented in training data. The framework is built for adaptability, supporting a wide array of machine learning models. ...

Esaote Unveils AI-Powered Cardiac Ultrasound at ESC 2025 for Enhanced Diagnostics Medical imaging company Esaote is set to introduce significant AI enhancements to its cardiac ultrasound technology at the European Society of Cardiology (ESC) 2025 conference. The system utilizes machine learning algorithms to improve image clarity and diagnostic accuracy. This innovation in AI-driven medical imaging aims to enhance cardiac workflows and enable quicker, more reliable interpretation of results for healthcare professionals. ...

Microsoft Challenges OpenAI with In-House MAI-1 and MAI-Voice-1 AI Models Microsoft has begun public testing for MAI-1, its first internally developed, large-scale AI model, marking a significant strategic move to reduce its reliance on partner OpenAI. The new foundational model is engineered for general-purpose tasks, including answering complex questions and following instructions. Alongside MAI-1, Microsoft also unveiled MAI-Voice-1, a sophisticated model capable of generating natural-sounding, human-like speech. The voice model can reportedly generate one minute of audio in under a second using minimal computing power. These releases signal escalating competition in the generative AI space, especially within multimodal and voice-based applications. ...