Statistics Up AI Alliance;International Chinese Statistical Association (ICSA);Xihong Lin,Tianxi Cai,David Donoho et al.
Statistics Up AI Alliance;International Chinese Statistical Association (ICSA);Xihong Lin et al.
A three-hour webinar titled "Statistics and AI - A Fireside Conversation" was held on Sunday, March 17th, 2024, attracting an online audience of approximately 1,000 attendees. The event featured three sessions aimed at engaging the statisti...
Nicholas Mirin,Heather Mattie,Latifa Jackson et al.
Nicholas Mirin et al.
Rapidly evolving technology, data, and analytic landscapes are permeating many fields and professions. In public health, the need for data science skills, including data literacy, is particularly prominent given both the potential of novel ...
Expanding the Data Science Toolkit: Mixed Methods for Improving Causal Inference [0.03%]
扩展数据科学工具包：改进因果推断的混合方法
Noor Qaragholi,Elizabeth A Stuart
Noor Qaragholi
Assessing the prognostic utility of clinical and radiomic features for COVID-19 patients admitted to ICU: challenges and lessons learned [0.03%]
评估临床和影像组学特征在COVID-19患者入住ICU后的预后价值：面临的挑战与经验教训
Yuming Sun,Stephen Salerno,Ziyang Pan et al.
Yuming Sun et al.
Severe cases of COVID-19 often necessitate escalation to the Intensive Care Unit (ICU), where patients may face grave outcomes, including mortality. Chest X-rays play a crucial role in the diagnostic process for evaluating COVID-19 patients...
Rafael A Irizarry
Rafael A Irizarry
As the demand for data scientists continues to grow, universities are trying to figure out how to best contribute to the training of a workforce. However, there does not appear to be a consensus on the fundamental principles, expertise, ski...
Learning Lessons on Reproducibility and Replicability in Large Scale Genome-Wide Association Studies [0.03%]
大规模全基因组关联研究中关于可重复性和可复制性的经验教训
Xihong Lin
Xihong Lin
Reproducibility and replicability play a pivotal role in science. The article reflects on reproducibility and replicability as they figure in large scale genome-wide association studies. Overall, we emphasize the importance of enhancing dat...
Why Do I Get Side Effects? Personalized (N-of-1) Trials for Statin Intolerance and the Nocebo Effect [0.03%]
为什么我会产生副作用？针对他汀类药物不耐受和诺西波效应的个性化（单个受试者）试验
James Philip Howard,Frances A Wood,Darrel P Francis
James Philip Howard
The ability of statins to reduce the morbidity and mortality of cardiovascular disease has ensured that they are among the most prescribed drugs in modern medicine. Unfortunately, most patients who start taking statins will end up stopping ...
Joyce P Samuel,Susan H Wootton
Joyce P Samuel
The ethical and regulatory oversight of any clinical activity related to human subjects is commonly determined based on its categorization as either clinical practice or research. Prominent bioethicists have criticized the traditional disti...
Evaluating Personalized (N-of-1) Trials in Rare Diseases: How Much Experimentation Is Enough? [0.03%]
罕见疾病中个性化（N-of-1）试验的评估：进行多少实验才足够？
Ken Cheung,Hiroshi Mitsumoto
Ken Cheung
For rare diseases, conducting large, randomized trials of new treatments can be infeasible due to limited sample size, and it may answer the wrong scientific questions due to heterogeneity of treatment effects. Personalized (N-of-1) trials ...
Christopher Schmid,Jiabei Yang
Christopher Schmid
We describe Bayesian models for data from N-of-1 trials, reviewing both the basics of Bayesian inference and applications to data from single trials and collections of trials sharing the same research questions and data structures. Bayesian...