Publications

The multifarious outcomes in this literature are inconsistent across studies and susceptible to selective reporting. The lack of standardization hinders the evaluation of replication validity for reported discoveries.

Distinct incremental improvements in survival have been achieved for ovarian cancer chemotherapy over time, with the possibility to achieve a doubling or more of time to mortality with platinum and taxane combinations, especially when intraperitoneal administration is used.

This chapter reports the findings and recommendations from a multidisciplinary workshop, including geneticists, epidemiologists, journal editors, and bioinformatics experts, that was sponsored by the Human Genome Epidemiology Network (HuGENet) and held in Atlanta on January 24-25, 2008. The meeting was convened in order to discuss synthesis and appraisal of cumulative evidence on genetic associations and to develop a strategy for an online encyclopedia on genetic variation and common human diseases.

The problem of cache coherence in shared-memory multiprocessors is addressed using two basic approaches: directory schemes and snoopy cache systems. Directory schemes for cache coherence are potentially attractive in large multiprocessor systems that are beyond the scaling limits of the snoopy cache schemes. Slight modifications to directory schemes can make them competitive in performance with snoopy cache schemes for small multiprocessors. Trace-driven simulation, using data collected from several real multiprocessor applications, is used to compare the performance of standard directory schemes, modifications to these schemes, and snoopy cache protocols. In addition, the simulations show that most blocks that are written into are present in only a small number of other caches, which makes broadcast invalidates inefficient. This result suggests that a directory structure that stores with each block only a small number of pointers to caches containing the block is sufficient.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Abstract Background It is unknown whether large language models (LLMs) may facilitate time- and resource-intensive text-related processes in evidence appraisal. Objectives To quantify the agreement of LLMs with human consensus in appraisal of scientific reporting (PRISMA) and methodological rigor (AMSTAR) of systematic reviews and design of clinical trials (PRECIS-2). To identify areas, where human-AI collaboration would outperform the traditional consensus process of human raters in efficiency. Design Five LLMs (Claude-3-Opus, Claude-2, GPT-4, GPT-3.5, Mixtral-8x22B) assessed 112 systematic reviews applying the PRISMA and AMSTAR criteria, and 56 randomized controlled trials applying PRECIS-2. We quantified agreement between human consensus and (1) individual human raters; (2) individual LLMs; (3) combined LLMs approach; (4) human-AI collaboration. Ratings were marked as deferred (undecided) in case of inconsistency between combined LLMs or between the human rater and the LLM. Results Individual human rater accuracy was 89% for PRISMA and AMSTAR, and 75% for PRECIS-2. Individual LLM accuracy was ranging from 63% (GPT-3.5) to 70% (Claude-3-Opus) for PRISMA, 53% (GPT-3.5) to 74% (Claude-3-Opus) for AMSTAR, and 38% (GPT-4) to 55% (GPT-3.5) for PRECIS-2. Combined LLM ratings led to accuracies of 75-88% for PRISMA (4-74% deferred), 74-89% for AMSTAR (6-84% deferred), and 64-79% for PRECIS-2 (18-88% deferred). Human-AI collaboration resulted in the best accuracies from 89-96% for PRISMA (25/35% deferred), 91-95% for AMSTAR (27/30% deferred), and 80-86% for PRECIS-2 (76/71% deferred). Conclusions Current LLMs alone appraised evidence worse than humans. Human-AI collaboration may reduce workload for the second human rater for the assessment of reporting (PRISMA) and methodological rigor (AMSTAR) but not for complex tasks such as PRECIS-2.

Richard Jaeger of Auburn University will be presented the IEEE Undergraduate Teaching Award 2004 for inspirational teaching at the ISSCC in San Francisco in Feb