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...
Emerging radar-based technologies for cuffless blood pressure monitoring-a systematic review [0.03%]
无袖带血压监测的雷达技术发展-系统综述
Debbie Falconer,Bernard Brincat,Michele Orini et al.
Debbie Falconer et al.
Hypertension is the leading risk factor for cardiovascular disease, the most common cause of death worldwide. Less than half the people with high blood pressure are aware of their diagnosis, and only a fifth are adequately treated. Because ...
The use of advanced machine learning to predict outcomes after atezolizumab plus bevacizumab for advanced hepatocellular carcinoma: a retrospective cohort study [0.03%]
利用先进机器学习预测阿特朱单抗联合贝伐珠单抗治疗晚期肝细胞癌的疗效：回顾性队列研究
Mathew Vithayathil,Giulia Francesca Manfredi,Antonio D&#x;Alessio et al.
Mathew Vithayathil et al.
Background: Combination immune checkpoint inhibitors are recommended as first-line therapy for advanced hepatocellular carcinoma. However, only a third of patients respond to treatment, and improved approaches to predict ...
When to and when not to use machine learning in risk prediction models [0.03%]
风险预测模型中机器学习的适用条件与限制条件分析
Lei Clifton,John Powell,David A Clifton et al.
Lei Clifton et al.
Mapping the susceptibility of large language models to medical misinformation across clinical notes and social media: a cross-sectional benchmarking analysis [0.03%]
大型语言模型在临床记录和社交媒体上对医学错误信息敏感性的地图绘制：横断面基准分析
Mahmud Omar,Vera Sorin,Lothar H Wieler et al.
Mahmud Omar et al.
Background: Large language models (LLMs) are increasingly used in health care but remain vulnerable to medical misinformation. We aimed to evaluate how often these models accept or reject fabricated medical content, and h...