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Exploring the feedback effects of incentive methods on HIV rapid self-testing among men who have sex with men in Chongqing, China
CONCLUSION: Our results show no significant differences in feedback rates across groups at follow-up time points. Significant differences in feedback rate trends among the three groups were observed, with the extra lottery incentive providing more sustained motivation for feedback. And privacy concerns are crucial for expanding HIVST among MSM via social apps. →
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Poziotinib for EGFR exon 20-insertion NSCLC: Clinical efficacy of the phase 2 ZENITH trial and differential impact of EGFR exon 20 insertion location on sensitivity
EGFRex20 insertions (EGFRex20ins) can be classified as near- and far-loop based on the insertion location, however, the impact of location on responses to various EGFR tyrosine kinase inhibitors (TKIs) is poorly understood. In vitro studies show that afatinib, poziotinib, and zipalertinib more potently inhibited near-loop than far-loop insertions, whereas mobocertinib has similar IC(50) in both… →
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Percutaneous Coronary Intervention in Multivessel Disease and Infarct-Related Cardiogenic Shock: A DanGer Shock Substudy
CONCLUSIONS: Immediate multivessel PCI was associated with 60% lower odds of all-cause mortality compared with culprit-only PCI. →
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Efficacy of In-office Bleaching Gel One Week After Mixing: A Randomized Clinical Trial
CONCLUSION: In-office dental bleaching with Opalescence Boost PF 40% remained effective, without differences in risk and intensity of TS and GI, even 1 week after mixing. →
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How to Build an End-to-End Data Science Workflow with Machine Learning, Interpretability, and Gemini AI Assistance?
«`html Understanding the Target Audience The target audience for this tutorial includes data scientists, machine learning engineers, and business analysts who are interested in building robust and interpretable data science workflows. These individuals typically work in technology-driven industries where data-driven decision-making is essential. Pain Points Difficulty in understanding and interpreting machine learning models Need for… →
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How LLMs Work: Top 10 Executive-Level Questions
Carolyn Geason-Beissel/MIT SMR | Getty Images In my work at MIT Sloan School of Management, I have taught the basics of how large language models (LLMs) work to many executives during the past two years. Some people posit that business leaders neither want to nor need to know how LLMs and the generative AI tools… →
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Clinical Interchangeability of PD-L1 Immunohistochemistry Assays in First-Line Non-Small Cell Lung Cancer Management With Cemiplimab
CONCLUSION: Similar efficacy (OS and PFS) was observed with the 22C3+ and SP263+ populations, demonstrating the interchangeability of these PD-L1 IHC assays for selecting patients with PD-L1 ≥50% for first-line cemiplimab monotherapy for advanced NSCLC. →
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Vision-RAG vs Text-RAG: A Technical Comparison for Enterprise Search
«`html Vision-RAG vs Text-RAG: A Technical Comparison for Enterprise Search Understanding the Target Audience The target audience for this comparison includes enterprise decision-makers, data scientists, and AI practitioners focused on enhancing document retrieval systems. Their pain points often revolve around inefficiencies in current retrieval methods, particularly in handling visually rich documents. They seek solutions that… →
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A randomised controlled trial to assess the feasibility and acceptability of remote psychosocial and exercise interventions for people with lupus: The ADAPT feasibility trial
Limited psychosocial support is available for people with lupus despite the highly reduced quality of life. This study assessed the acceptability, feasibility, and effectiveness estimations, of three (two psychosocial, one exercise) interventions. Lupus patients (N = 124) were randomised to a control arm or one of three interventions delivered remotely over 8-12 weeks: (1) listening… →
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Multimodal prognostic modeling of individual cognitive trajectories to enhance trial efficiency in preclinical Alzheimer’s disease
INTRODUCTION: Cognitive decline in asymptomatic preclinical Alzheimer’s disease (AD) is slow and variable, limiting detection of treatment effects. This study developed models to forecast trajectories and improve trial efficiency. →
