A novel AI-powered radiographic analysis surpasses specialists in stage II-IV periodontitis detection: a multicenter diagnostic study [0.03%]
一种新型AI驱动的放射影像分析在二期至四期牙周炎检测中超越专科医师：一项多中心诊断研究
Yuan Li,Zhiming Cui,Lanzhuju Mei et al.
Yuan Li et al.
Missed periodontitis diagnoses are common, and AI dental radiography systems based on clinical standards can enhance reliable detection. We introduce and evaluate HC-Net+, a deep-learning model that mimics clinical pathways while integratin...
Juzhao Zhang,Senlin Lin,Haidong Zou et al.
Juzhao Zhang et al.
This reply addresses Chan et al.'s comments on our previous study, clarifying the use of foundation models (e.g., RETFound), commercial data sources/anonymity, and DeLong test results. We highlight that the SDEDS-fine-tuned RETFound outperf...
An artificial intelligence system for qualified mucosal observation time during colonoscopic withdrawal [0.03%]
一种评估结肠镜退回过程中黏膜观察质量的人工智能系统
Wu-Jun Li,Peng Yan,Muhan Ni et al.
Wu-Jun Li et al.
Colonoscopic withdrawal time is crucial for achieving a high adenoma detection rate (ADR) and reducing post-colonoscopy colorectal cancer risk. Enhanced qualified mucosal observation improves ADR, but manual quantification of qualified muco...
Deep learning-enabled multiphoton microscopy predicts colorectal cancer recurrence from routine FFPE specimens [0.03%]
深度学习介导的多光子显微镜技术可预测常规福尔马林固定石蜡包埋样本中的结直肠癌复发
Yabing Yang,Chanchan Xiao,Dehua Zou et al.
Yabing Yang et al.
Colorectal cancer recurrence remains a major challenge after curative resection, and accurate tools for early risk assessment are essential to stratify patients and guide personalized therapeutic planning. We developed MPMRecNet, a dual-str...
Enhancing post-kidney transplant prognostication: an interpretable machine learning approach for longitudinal outcome prediction [0.03%]
可解释的机器学习在肾移植后预后中的应用：纵向结局预测的方法研究
Bowen Fan,Manuel Schürch,Yuan Tian et al.
Bowen Fan et al.
Kidney transplantation offers life-extending treatment for patients with end-stage renal disease, yet long-term risks of graft loss and death persist. Traditional prediction models using only baseline data often fail to capture patients' ev...
Quantifying Early-Stage Lung Adenocarcinoma Progression with a Radiomic Trajectory [0.03%]
基于影像组学的肺腺癌进展轨迹量化研究
Zhen-Bin Qiu,Jiaqi Li,Shihua Dou et al.
Zhen-Bin Qiu et al.
Determining tumor progression status is critical for early-stage lung adenocarcinoma (esLUAD) diagnosis and treatment, yet histopathology-based grading often overlooks heterogeneity within grades. We propose RadioTrace, a deep contrastive l...
Evaluation of the Allergy Fact Checker, a clinical decision support system for non-invasive beta-lactam delabeling: a mixed-methods study [0.03%]
过敏事实核查者评价：一种关于非侵入性青霉素再标签的临床决策支持系统：一种混合方法研究
Greet Van De Sijpe,Liesbeth Gilissen,Dries Wets et al.
Greet Van De Sijpe et al.
Penicillin allergy delabeling strategies are time- and resource-consuming. In this mixed-methods study, we evaluated the 'Allergy Fact Checker', a novel clinical decision support system designed to identify patients with uneventful re-expos...
A tree-structured multiobjective optimization framework for constructing diagnosis-related groups [0.03%]
一种用于构建相关病组的树型多目标优化框架
Gaocheng Cai,Zhimei Zeng,Mengjie Wan et al.
Gaocheng Cai et al.
The effectiveness of diagnosis-related groups (DRG) system is pivotal to the implementation of medical insurance payment standards. However, existing methods for constructing DRGs face challenges such as violations of grouping rules and imb...
Development of a deep learning-based prediction model for postoperative delirium using intraoperative electroencephalogram in adults [0.03%]
基于深度学习的术后谵妄预测模型的开发使用成人患者的术中脑电图数据
Jang Ho Ahn,Hyeonhoon Lee,Pedro Gambus et al.
Jang Ho Ahn et al.
Postoperative delirium (POD) is associated with increased morbidity and mortality. This study aims to develop a deep learning-based model (DELPHI-EEG) to predict postoperative delirium using intraoperative electroencephalogram (EEG) wavefor...
A multimodal AI model for precision prognosis in clear cell renal cell carcinoma: A multicenter study [0.03%]
一种用于透明细胞肾细胞癌精准预后的多模态AI模型：一项多中心研究
Xinyi Zang,Yujia Xia,Haibing Xiao et al.
Xinyi Zang et al.
Patients with clear cell renal cell carcinoma (ccRCC) face a high risk of recurrence after surgery, but existing clinical tools based on clinicopathological factors or costly molecular profiling often lack precision and clinical feasibility...