Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered ...
Data Normalization vs. Standardization is one of the most foundational yet often misunderstood topics in machine learning and data preprocessing. If you''ve ever built a predictive model, worked on a ...
Introduction Perinatal depression poses substantial risks to both mothers and their offspring. Given its chronic and ...
BACKGROUND: Mental stress-induced myocardial ischemia is often clinically silent and associated with increased cardiovascular risk, particularly in women. Conventional ECG-based detection is limited, ...
The CMS Collaboration has shown, for the first time, that machine learning can be used to fully reconstruct particle ...
Explore how machine learning in insurance enhances risk assessment, fraud detection, and personalization. ✓ Subscribe for ...
Umbrella or sun cap? Buy or sell stocks? When it comes to questions like these, many people today rely on AI-supported recommendations. Chatbots such as ChatGPT, AI-driven weather forecasts, and ...
When everyone has access to the same AI models, the same AI-enabled tools, and the same vendor ecosystem, organizational ...
Large language models (LLMs) can suggest hypotheses, write code and draft papers, and AI agents are automating parts of the research process. Although this can accelerate science, it also makes it ...
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Why AI may overcomplicate answers: Humans and LLMs show 'addition bias,' often choosing extra steps over subtraction
When making decisions and judgments, humans can fall into common "traps," known as cognitive biases. A cognitive bias is ...
Background Motor and cognitive dysfunctions are common and disabling features in multiple sclerosis (MS) that remain challenging to treat. Here, we aimed to explore the effect of exergames as a ...
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