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Comparative Analysis of Cardiac CT and Invasive Coronary Angiography for Suspected Stable Coronary Artery Disease and Subsequent Functional Testing and Revascularization: A Prespecified Secondary DISCHARGE Randomized Trial Analysis
Purpose To compare functional testing and management after cardiac CT-first versus invasive coronary angiography (ICA)-first strategies in participants with stable chest pain and low to intermediate probability of obstructive coronary artery disease (CAD) initially referred for ICA. Materials and Methods This study was a prespecified secondary analysis of the prospective, multicenter, randomized DISCHARGE (Diagnostic Imaging… →
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Adding L-Carnitine and Selenium to Methimazole in Graves’ Disease: A Prospective Randomized Trial on Thyroid Markers and Quality of Life
Background: The therapeutic response in Graves’ Disease (GD) remains largely unpredictable. Patients often experience persistent symptoms that are poorly correlated with thyroid hormone levels, an undefined treatment duration, and the need for long-term or definitive therapies. Based on the nuclear antagonistic properties of L-carnitine (LCT) on thyroid hormone action and the immunomodulatory role of selenium… →
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Grounding Medical AI in Expert‑Labeled Data: A Case Study on PadChest-GR- the First Multimodal, Bilingual, Sentence‑Level Dataset for Radiology Reporting
«`html Grounding Medical AI in Expert-Labeled Data: A Case Study on PadChest-GR A Multimodal Radiology Breakthrough Recent advances in medical AI have underscored that breakthroughs hinge not solely on model sophistication, but fundamentally on the quality and richness of the underlying data. This case study spotlights a pioneering collaboration among Centaur.ai, Microsoft Research, and the… →
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How to Build a Multi-Round Deep Research Agent with Gemini, DuckDuckGo API, and Automated Reporting?
«`html How to Build a Multi-Round Deep Research Agent with Gemini, DuckDuckGo API, and Automated Reporting In this tutorial, we will design a modular deep research system that operates directly on Google Colab. The system will utilize Gemini as the core reasoning engine, integrate DuckDuckGo’s Instant Answer API for lightweight web searches, and orchestrate multi-round… →
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Australia’s Large Language Model Landscape: Technical Assessment
«`html Australia’s Large Language Model Landscape: Technical Assessment Understanding the Target Audience The target audience for this assessment includes AI researchers, business leaders, policymakers, and academic professionals in Australia. Their pain points involve the reliance on international large language models (LLMs) that often lack alignment with Australian English and cultural nuances. Additionally, they seek solutions… →
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Nous Research Team Releases Hermes 4: A Family of Open-Weight AI Models with Hybrid Reasoning
Nous Research Team Releases Hermes 4: A Family of Open-Weight AI Models with Hybrid Reasoning Nous Research has introduced Hermes 4, a family of open-weight models (14B, 70B, and 405B parameter sizes based on Llama 3.1 checkpoints) that achieves frontier-level performance through post-training techniques. Hermes 4 features hybrid reasoning, allowing models to switch between standard… →
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A Coding Implementation of Quantum State Evolution, Decoherence, and Entanglement Dynamics using QuTiP
«`html A Coding Implementation of Quantum State Evolution, Decoherence, and Entanglement Dynamics using QuTiP In this advanced QuTiP tutorial, we explore the rich dynamics of quantum systems using Python and the QuTiP framework. We’ll begin by preparing fundamental single- and two-qubit states, including Bell pairs, and then move on to implement key quantum operations such… →
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Four Traits of Forward-Looking CEOs
Grundini/Ikon Images A profound shift is underway in global leadership. Organizations are confronting technological disruption, geopolitical risk, climate urgency, and rapidly evolving social expectations. It’s clear that the leadership models of the past — built on hierarchy, control, and confidence about how the future will unfold — are no longer fit for purpose. I’ve both… →
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What is Agentic RAG? Use Cases and Top Agentic RAG Tools (2025)
«`html What is Agentic RAG? Use Cases and Top Agentic RAG Tools (2025) What is Agentic RAG? Agentic RAG combines the strengths of traditional retrieval-augmented generation (RAG) with agentic decision-making and tool use. Unlike static approaches, agentic RAG features AI agents that orchestrate retrieval, generation, query planning, and iterative reasoning. These agents autonomously choose data… →