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Ultrasound-Guided Pleural Needle Biopsy Which Needle for Which Patient: A Prospective Randomized Study
CONCLUSION: US-CNPB should be preferred in patients with pleural thickness ≥ 1 cm on US. MT is recommended for patients with pleural thickening < 1 cm or those presenting with pleural effusion without pleural thickening. However, in the absence of MT, US-ANPB is the preferred alternative because of its superior diagnostic accuracy and procedural safety. →
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Impact of RoSCo-based preoperative risk stratification on early mobilization and short-term outcomes following robot-assisted laparoscopic partial nephrectomy for renal cell carcinoma: a single-center prospective study
This study aimed to evaluate the effectiveness of the RoSCo preoperative risk scoring system, which incorporates the RENAL Nephrometry Score, the Charlson’s Comorbidity Index, and body mass index to quantify surgical risk, in guiding individualized early mobilization protocols and to assess associated early postoperative recovery outcomes in patients undergoing robot-assisted partial nephrectomy (RAPN) for renal… →
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Endobiliary radiofrequency ablation in recurrence and unresectable Perihilar cholangiocarcinoma
CONCLUSION: The EBRFA, when combined with SEMS placement, demonstrated procedural feasibility and acceptable outcomes as a potential palliative approach for patients with unresectable pCCA. →
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ByteDance Just Released Trae Agent: An LLM-based Agent for General Purpose Software Engineering Tasks
«`html ByteDance Just Released Trae Agent: An LLM-based Agent for General Purpose Software Engineering Tasks ByteDance, the Chinese tech giant behind TikTok and other global platforms, has officially released Trae Agent, a general-purpose software engineering agent powered by large language models (LLMs). Designed to execute complex programming tasks via natural language prompts, Trae Agent offers… →
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Getting Started with Agent Communication Protocol (ACP): Build a Weather Agent with Python
Getting Started with Agent Communication Protocol (ACP): Build a Weather Agent with Python Getting Started with Agent Communication Protocol (ACP): Build a Weather Agent with Python The Agent Communication Protocol (ACP) is an open standard designed to enable seamless communication between AI agents, applications, and humans. As AI systems are often developed using diverse frameworks… →
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SynPref-40M and Skywork-Reward-V2: Scalable Human-AI Alignment for State-of-the-Art Reward Models
Understanding Limitations of Current Reward Models Although reward models are crucial in Reinforcement Learning from Human Feedback (RLHF), many of today’s top-performing open models struggle to reflect the full range of complex human preferences. Even with advanced training techniques, meaningful progress has been limited. A major reason for this is the shortcomings in current preference… →
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New AI Method From Meta and NYU Boosts LLM Alignment Using Semi-Online Reinforcement Learning
«`html New AI Method From Meta and NYU Boosts LLM Alignment Using Semi-Online Reinforcement Learning Understanding the Target Audience The target audience for this research includes AI researchers, data scientists, business managers, and decision-makers in technology firms. Their pain points revolve around the challenges of aligning large language models (LLMs) with human expectations, optimizing model… →
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Efficacy and safety of immunosuppressive therapy versus cyclosporine combined with avatrombopag in older adults with severe aplastic anemia: a multicenter prospective study
This trial compared antithymocyte globulin (ATG) + cyclosporine A (CsA) + avatrombopag (AVA) and CsA + AVA in older adults with severe aplastic anemia (SAA). The patients were randomized to receive either ATG + CsA + AVA or CsA + AVA. Of 84 included patients, 42 were treated with ATG + CsA + AVA and… →
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What Is Context Engineering in AI? Techniques, Use Cases, and Why It Matters
«`html What Is Context Engineering in AI? Techniques, Use Cases, and Why It Matters Introduction: What is Context Engineering? Context engineering refers to the discipline of designing, organizing, and manipulating the context that is fed into large language models (LLMs) to optimize their performance. This practice focuses on the input—the prompts, system instructions, retrieved knowledge,… →
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A Coding Guide to Build Modular and Self-Correcting QA Systems with DSPy
A Coding Guide to Build Modular and Self-Correcting QA Systems with DSPy In this tutorial, we explore how to build an intelligent and self-correcting question-answering system using the DSPy framework, integrated with Google’s Gemini 1.5 Flash model. We begin by defining structured Signatures that clearly outline input-output behavior, which DSPy uses as its foundation for… →