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Factors Associated With Self-Report Symptom Screening Adherence in Pediatric Cancer Patients
CONCLUSION: Adherence to three-times weekly SSPedi varied by age, race, ethnicity, cancer diagnosis, and family income. This information may facilitate interventions to support routine symptom screening in clinical practice. →
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The Evaluation of Memantine Effect on Tinnitus Severity
CONCLUSION: On the basis of these findings, it is suggested that memantine may have remarkable effect in reducing tinnitus and its discomfort. →
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Intensive Blood Pressure Control in Patients With Diabetes and Previous Stroke: A Post-Hoc Analysis of ACCORD-BP Trial
Intensive systolic blood pressure (SBP) control reduces cardiovascular outcomes in hypertensive patients, but its effects in those with diabetes and prior stroke need further evidence. Among 4733 patients with elevated SBP enrolled in the ACCORD-BP (Action to Control Cardiovascular Risk in Diabetes-Blood Pressure) trial, this post-hoc analysis focused on 307 patients with type 2 diabetes… →
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TikTok Researchers Introduce SWE-Perf: The First Benchmark for Repository-Level Code Performance Optimization
TikTok Researchers Introduce SWE-Perf: The First Benchmark for Repository-Level Code Performance Optimization Introduction As large language models (LLMs) advance in software engineering tasks—ranging from code generation to bug fixing—performance optimization remains an elusive frontier, especially at the repository level. To bridge this gap, researchers from TikTok and collaborating institutions have introduced SWE-Perf—the first benchmark specifically… →
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Allen Institute for AI-Ai2 Unveils AutoDS: A Bayesian Surprise-Driven Engine for Open-Ended Scientific Discovery
Allen Institute for AI-Ai2 Unveils AutoDS: A Bayesian Surprise-Driven Engine for Open-Ended Scientific Discovery The Allen Institute for Artificial Intelligence (AI2) has introduced AutoDS (Autonomous Discovery via Surprisal), a prototype engine for open-ended autonomous scientific discovery. Unlike traditional AI research assistants that rely on human-defined objectives, AutoDS autonomously generates, tests, and iterates on hypotheses by… →
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Building a Smart Python-to-R Code Converter with Gemini AI-Powered Validation and Feedback
«`html Understanding the Target Audience The target audience for the tutorial on building a smart Python-to-R code converter using Gemini AI includes data scientists, software developers, and business analysts. These professionals often work in environments that require the integration of multiple programming languages for data analysis and statistical processing. Pain Points Difficulty in converting code… →
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Impact of root canal shaping using TruNatomy on postoperative pain and operative torque generation: a randomized clinical trial
CONCLUSION: TN and RC rotary instruments resulted in similar and acceptable levels of post-operative pain in cases of asymptomatic necrotic teeth. However, TN rotary system combined torque and instrumentation time values suggest an overall higher cutting efficiency and potentially a better safety profile as compared to RC rotary system. →
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MIRIX: A Modular Multi-Agent Memory System for Enhanced Long-Term Reasoning and Personalization in LLM-Based Agents
«`html MIRIX: A Modular Multi-Agent Memory System for Enhanced Long-Term Reasoning and Personalization in LLM-Based Agents Persona & Context Understanding The target audience for MIRIX includes AI developers, business managers, and organizational leaders interested in implementing advanced AI solutions. Their pain points often revolve around the limitations of current LLM agents, specifically the lack of… →
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Can LLM Reward Models Be Trusted? Master-RM Exposes and Fixes Their Weaknesses
Can LLM Reward Models Be Trusted? Master-RM Exposes and Fixes Their Weaknesses Can LLM Reward Models Be Trusted? Master-RM Exposes and Fixes Their Weaknesses Generative reward models, where large language models (LLMs) serve as evaluators, are gaining prominence in reinforcement learning with verifiable rewards (RLVR). These models are preferred over rule-based systems for tasks involving… →
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Model Context Protocol (MCP) for Enterprises: Secure Integration with AWS, Azure, and Google Cloud- 2025 Update
«`html Model Context Protocol (MCP) for Enterprises: Secure Integration with AWS, Azure, and Google Cloud — 2025 Update MCP Overview & Ecosystem The Model Context Protocol (MCP) is an open standard based on JSON-RPC 2.0 designed to enable AI systems, such as large language models, to securely discover and interact with functions, tools, APIs, or… →