randomized controlled trial
PulseAugur coverage of randomized controlled trial — every cluster mentioning randomized controlled trial across labs, papers, and developer communities, ranked by signal.
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AI/ML clinical trials analysis reveals study trends from 2010-2023
A comprehensive analysis of AI and ML clinical trials conducted between 2010 and 2023 has been published, examining 3106 studies. The findings indicate that 56.2% of these trials were randomized, with 44.2% sponsored by…
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New roadmap integrates RCTs, RWD, and AI/ML for evidence synthesis
A new perspective paper proposes a six-step statistical roadmap for integrating randomized controlled trials (RCTs), real-world data (RWD), and artificial intelligence/machine learning (AI/ML) to improve evidence synthe…
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AI and Real-World Evidence Accelerate Rare Disease Treatment Development
Artificial intelligence (AI) and real-world evidence (RWE) are converging to accelerate the development of treatments for rare diseases. Traditional clinical trials are often impractical for these conditions due to smal…
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New CALM method aligns RCT and observational data for better treatment effect estimation
Researchers have developed CALM (Calibrated ALignment under covariate Mismatch), a novel method for improving treatment effect estimation by aligning data from randomized controlled trials (RCTs) and observational studi…
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ChatGPT explored for improving clinical trial efficiency
Researchers explored using ChatGPT to improve randomized controlled trials (RCTs), which are typically expensive and time-consuming. The goal was to find a more efficient solution for conducting these trials.
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AI evaluation studies face validity challenges, paper finds
A new paper published on arXiv details methodological challenges in evaluating frontier AI systems through human uplift studies. These studies, which use randomized controlled trials to measure AI's impact on human perf…
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New study design tackles unobserved confounding in observational data
Researchers have introduced a novel study design called "confounder detection via treatment intent" to address unobserved confounding in observational data. This method involves querying human experts to identify unobse…