Identification of drug repurposing candidates for amyotrophic lateral sclerosis using electronic health records: a retrospective cohort study [0.03%]
基于电子健康记录识别肌萎缩侧索硬化症药物再定位候选药物的回顾性队列研究
Richard J Reimer,Braden Soper,Jennifer L Wilson et al.
Richard J Reimer et al.
Background: Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disease with a life expectancy of only 3-5 years and few approved treatments. To identify drug repurposing candidates for the treatment of...
The Lancet Digital Health
The Lancet Digital Health
Artificial intelligence-based pathological model for pan-cancer lymph node metastasis detection: a multicentre diagnostic study with retrospective and prospective validation [0.03%]
基于人工智能的病理模型用于泛癌淋巴结转移检测：一项多中心诊断研究及其回顾性和前瞻性验证
Shaoxu Wu,Guibin Hong,Yun Wang et al.
Shaoxu Wu et al.
Background: Accurate detection of lymph node metastasis is crucial for precise tumour staging and treatment planning. Conventional pathological examination can overlook lymph node micrometastasis, resulting in underdiagno...
The need to develop health data transaction disclosure requirements to balance transparency, privacy, and progressive use [0.03%]
开发健康数据交易披露要求以平衡透明度、隐私和进步利用的需求
Matthew G Crowson,Jade Z H Tan,Jessilyn Dunn et al.
Matthew G Crowson et al.
This Viewpoint critically evaluates the impact of commodifying health data in the era of electronic health records and the ethical challenges this practice raises. Additionally, the Viewpoint explores the complex interplay between the advan...
Michael Ingrisch
Michael Ingrisch
AI-based BRAIx risk score for the intermediate-term prediction of breast cancer: a population cohort study [0.03%]
基于人工智能的BRAIx风险评分在乳腺癌中期预测中的应用：一项人口队列研究
Helen M L Frazer,John L Hopper,Tuong L Nguyen et al.
Helen M L Frazer et al.
Background: Artificial intelligence (AI)-based algorithms are being implemented in breast screening to detect breast cancers on mammographic images. We aimed to apply an epidemiological approach to demonstrate how a cance...
RareArena: a comprehensive benchmark dataset unveiling the potential of large language models in rare disease diagnosis [0.03%]
RareArena：一个全面的基准数据集，揭示了大型语言模型在罕见病诊断中的潜力
Haichao Chen,Zhengyun Zhao,Songchi Zhou et al.
Haichao Chen et al.
Rare diseases pose a substantial clinical and public health burden, with timely and accurate diagnoses remaining a formidable challenge in many countries and settings. Large language models (LLMs) have the potential to enhance the screening...
End-to-end integrative segmentation and radiomics prognostic models for risk stratification of high-grade serous ovarian cancer: a retrospective multicohort study [0.03%]
高分期浆液性卵巢癌的端到端整合分割和影像组学预后模型的多队列回顾性研究
Kristofer Linton-Reid,Haonan Lu,Georg Wengert et al.
Kristofer Linton-Reid et al.
Background: Valid stratification factors for patients with epithelial ovarian cancer are still lacking and individualisation of care remains an unmet need. Radiomics derived from routine contrast enhanced CT (CE-CT) is an...
Agentic artificial intelligence in eye care: is clinical autonomy finally within reach? [0.03%]
代理型人工智能在眼科护理中的应用：临床自主性终于触手可及了吗？
Ke Zou,Jocelyn Hui Lin Goh,Gabriel Dawei Yang et al.
Ke Zou et al.
Large language models for simplifying radiology reports: a systematic review and meta-analysis of patient, public, and clinician evaluations [0.03%]
简化放射学报告的大型语言模型系统评价和元分析：患者、公众及临床医生的评估
Samer Alabed,Abigail Anderson,Ahmed Maiter et al.
Samer Alabed et al.
Background: Radiology reports are typically written in language that is difficult for patients to understand. Large language models (LLMs) excel at simplifying text. We aimed to evaluate the ability of LLMs to improve the...