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Validity and usability for digital cognitive assessment tools to screen for mild cognitive impairment: a randomized crossover trial
CONCLUSIONS: Digital cognitive tests are valid and feasible in PHC settings but face implementation challenges, especially in usability and adaptability among individuals with lower education levels. →
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A large-scale multimodal investigation of the interplay between the serotonergic system and emotion processing
Considering the complexity of serotonergic influence on emotions, we conducted a comprehensive investigation of the interplay between emotion processing and the serotonergic system using simultaneous functional and molecular neuroimaging during pharmacological challenge while disentangling the effects of serotonin transporter (SERT) binding, genotype, and diagnosis of major depressive disorder (MDD). Herein, 153 subjects (44 with MDD)… →
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Awareness of baseline functioning and sensitivity to improvement in older people with and without mild cognitive impairment receiving a computerized functional skills training program
CONCLUSIONS: Participants with MCI underestimated their performance deficits at baseline. Self-reports of changes in everyday functioning do not track the substantial objective changes. Previous studies have reported a lack of sensitivity to training gains in several different conditions. Strategies to increase awareness of training gains may be required to sustain treatment benefits. →
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Systemic indocyanine green administration to detect bile leakage after liver surgery: a prospective clinical trial, using historical controls
CONCLUSIONS: Intraoperative ICG administration and assessment effectively lower bilirubin levels in drainage fluid during hepatectomy, potentially reducing the incidence of BL. →
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Run Multiple AI Coding Agents in Parallel with Container-Use from Dagger
Run Multiple AI Coding Agents in Parallel with Container-Use from Dagger Understanding the Target Audience The target audience for the topic of running multiple AI coding agents in parallel using container-use from Dagger primarily consists of developers, team leads, and project managers in tech organizations. These individuals are likely engaged in software development, particularly in… →
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Training AI to Detect Disease: Stand Up To Cancer’s Julian Adams
Julian Adams tried but didn’t succeed at retirement after a productive career as a medical chemist with several U.S. Food and Drug Administration approvals of cancer-related treatments, including cell therapy for bone marrow transplantation. Soon after, his participation in a Stand Up To Cancer advisory group led to his appointment as the nonprofit’s president and… →
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CURE: A Reinforcement Learning Framework for Co-Evolving Code and Unit Test Generation in LLMs
«`html CURE: A Reinforcement Learning Framework for Co-Evolving Code and Unit Test Generation in LLMs Introduction Large Language Models (LLMs) have shown substantial improvements in reasoning and precision through reinforcement learning (RL) and test-time scaling techniques. Despite outperforming traditional unit test generation methods, most existing approaches such as O1-Coder and UTGEN require supervision from ground-truth… →
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Develop a Multi-Tool AI Agent with Secure Python Execution using Riza and Gemini
«`html Develop a Multi-Tool AI Agent with Secure Python Execution using Riza and Gemini In this tutorial, we’ll harness Riza’s secure Python execution as the cornerstone of a powerful, tool-augmented AI agent in Google Colab. We will begin with seamless API key management through Colab secrets, environment variables, or hidden prompts to configure your Riza… →
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How Do LLMs Really Reason? A Framework to Separate Logic from Knowledge
How Do LLMs Really Reason? A Framework to Separate Logic from Knowledge Understanding the Target Audience The target audience for this content primarily comprises AI researchers, business managers, and professionals in fields such as healthcare and finance who are interested in the functioning and evaluation of large language models (LLMs). These readers are typically involved… →
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Development and validation of a nomogram for predicting the clearance of jaundice in children with biliary Atresia after Kasai portoenterostomy
CONCLUSION: This study developed and validated a nomogram incorporating four indictors, including Age at KPE, postoperative AST level at two weeks, CR of DB at two weeks post-KPE and F-score at KPE, may be useful for predicting CJ at 3 months after KPE in children with BA. →
