Large language models as experimental systems in human psychopathology: a modelling study [0.03%]
大型语言模型在人类精神病学中的实验系统研究：一种建模方法
Magdalena Katharina Wekenborg,Elizabeth Anna Mathilde Michels,Georg Kurze et al.
Magdalena Katharina Wekenborg et al.
Background: Despite advances in biomedical research, human psychopathology remains underserved by experimental model systems, limiting therapeutic innovation. Alternative approaches are needed to investigate the mechanism...
Beyond language: generative artificial intelligence as a general computing model for medicine [0.03%]
超越语言：医学领域的生成式人工智能通用计算模型
Arkadiusz Sitek,David W Bates
Arkadiusz Sitek
In this Viewpoint, we advocate for direct tokenisation of medical data by breaking them into discrete units, such as laboratory results, medications, and vital signs, similar to word tokenisation in language models. This approach enables tr...
Deep learning for H&E-based meningioma molecular classification and outcome prediction: a retrospective cohort study [0.03%]
基于HE的脑膜瘤分子分类和结果预测的深度学习：一项回顾性队列研究
Alexander P Landry,Farshad Nassiri,Leeor S Yefet et al.
Alexander P Landry et al.
Background: The introduction of genomic profiling as a tool for molecular classification and clinical outcome prediction has revolutionised the care of patients with brain tumours. Artificial intelligence (AI) provides ad...
Development, validation, and user-centric evaluation of an interpretable machine learning decision support tool for the preoperative prediction of mild bleeding disorders (MBD-Check): a prospective diagnostic prediction study [0.03%]
一种可解释的机器学习决策支持工具的发展、验证及以用户为中心的评估：用于术前轻度出血性疾病预测（MBD-Check）：前瞻性诊断预测研究
Henning Nilius,Jonas Kaufmann,Marcel Adler et al.
Henning Nilius et al.
Background: Mild bleeding disorders are the most common inherited bleeding disorders, often leading to perioperative haemorrhages. Preoperative screening for mild bleeding disorders remains challenging due to the limitati...
Sustainability of large-scale artificial intelligence models in health care [0.03%]
医疗保健领域大规模人工智能模型的可持续性
Raghavendra Selvan
Raghavendra Selvan
Critical appraisal of fairness metrics for artificial intelligence-based clinical prediction models: a scoping review [0.03%]
对基于人工智能的临床预测模型公平性指标的批判性评价：系统综述
João Matos,Ben Van Calster,Leo Anthony Celi et al.
João Matos et al.
Predictive artificial intelligence (AI) offers an opportunity to improve clinical practice and patient outcomes but risks perpetuating biases if fairness is inadequately addressed. However, the definition of fairness remains unclear. We con...
Artificial intelligence analysis of temporalis muscle thickness for monitoring sarcopenia and clinical outcomes in individuals with paediatric brain tumours: a retrospective cohort study [0.03%]
人工智能分析咬肌厚度以监测儿童脑肿瘤患者的肌肉减少症和临床结局：一项回顾性队列研究
Anna Zapaishchykova,John Zielke,Divyanshu Tak et al.
Anna Zapaishchykova et al.
Background: People with and who have survived paediatric brain tumour (PBT) have a poor quality of life due to physiological frailty, a primary component of which is sarcopenia (ie, low lean muscle mass) and the associate...
Co-intelligence: a proposal for human-artificial intelligence collaboration for large language models in medical research [0.03%]
共智：大型语言模型在医学研究中的人工智能与人类协作提案
Ariel Yuhan Ong,David A Merle,Nigam H Shah et al.
Ariel Yuhan Ong et al.
The emergence of large language models (LLMs) offers transformative potential for medical research. Current approaches often focus on LLMs as a replacement for researchers or as a supporting tool. In this Viewpoint, we discuss the concept o...
Navigating the promise and pitfalls of dashboards in health policy decision making: experiences from Ghana, India, and South Africa [0.03%]
卫生决策过程中的仪表板承诺与陷阱：加纳、印度和南非的经验教训
Luxsena Sukumaran,Kwame S Sakyi,Vrashali Khandelwal et al.
Luxsena Sukumaran et al.
Dashboards and other interactive web-based data visualisation tools are increasingly being developed to inform health policy at global, national, and subnational levels. Dashboards aim to make policy-relevant data accessible to support deci...
Effects of large language model-generated, patient-oriented discharge summaries on patient activation: a single-centre, single-blind, randomised controlled trial in Germany [0.03%]
基于大型语言模型的以患者为中心的出院总结对德国患者的激活效应：单中心盲法随机对照试验
Paul Rust,Julian Frings,Sven Meister et al.
Paul Rust et al.
Background: The transition from hospital to home represents an important period in patient care. Evidence suggests that improving patient activation (knowledge, skills, and confidence in self-care) reduces adverse post-di...