A machine learning model incorporating functional assessments predicts one-year mortality in older patients with HF and improves risk stratification beyond established scores. Functional status at ...

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 ...

Objective: This study aims to explore patients’ experiences using the digital platform 1177-direkt for chat-based consultations in Swedish primary health care, with a focus on understanding their ...

Abstract: As technology scales to smaller nanometer nodes, Electromigration (EM) has become one of the most significant challenges in the EDA industry. Due to the reduction of the interconnect ...

Abstract: The high prevalence of diabetes mellitus, along with its asymptomatic onset in the early stages, poses significant challenges in the field of public health. Data-driven exploratory studies ...

Dive deep into Nesterov Accelerated Gradient (NAG) and learn how to implement it from scratch in Python. Perfect for improving optimization techniques in machine learning! 💡🔧 #NesterovGradient ...

Jan 10 (Reuters) - Elon Musk said on Saturday that social media platform X will open to the public its new algorithm, including all code for organic and advertising post recommendations, in seven days ...

OpenAI continues its push into healthcare with the launch of ChatGPT Health, a new feature that connects its artificial intelligence chatbot with users' medical records and wellness apps for more ...

The names and addresses of thousands of patients of the Illinois Department of Human Services were incorrectly made publicly viewable for the last several years, the agency said Friday. Several maps ...