Integrating deep learning in optical microscopy enhances image analysis, overcoming traditional limitations and improving classification and segmentation tasks.
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Mistaken correlations: Why it's critical to move beyond overly aggregated machine-learning metrics
MIT researchers have identified significant examples of machine-learning model failure when those models are applied to data other than what they were trained on, raising questions about the need to ...
Traditional processes used to discover new materials are complex, time-consuming, and costly, often requiring years of ...
Google has released TranslateGemma, a set of open translation models based on the Gemma 3 architecture, offering 4B, 12B, and ...
Google DeepMind researchers have introduced ATLAS, a set of scaling laws for multilingual language models that formalize how ...
AI chatbots, including commercial market leaders such as ChatGPT, Google Gemini, and Claude, dispense advice that heavily ...
Integrative Multi-Omics and Computational Modeling for Biomarker Discovery in Complex Human Diseases
Complex human diseases—such as cancer, neurodegenerative disorders, autoimmune conditions, cardiometabolic disease, and chronic inflammatory syndromes—arise ...
Triage, Critical Clinical Workflow Process, Chest Pain, Electrocardiogram (EKG), Door-to-EKG (DTE) Time Share and Cite: ...
Artificial Intelligence is everywhere, from shopping assistants on Amazon, to replacing search engines like Google. While ChatGPT might make it easy to put together a shopping list or travel plans, it ...
The number of complaints received by healthcare organisations from patients and families is on an upward trajectory.1 For example, in 2023–2024, the NHS in England received 241 922 complaints,2 an ...
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