Automatic segmentation of 15 critical anatomical labels and measurements of cardiac axis and cardiothoracic ratio in fetal four chambers using nnU-NetV2 [0.03%]
基于nnu-netv2的胎儿四腔心切面自动分割15种关键解剖结构及心脏轴、心胸比率量化测量方法
Bocheng Liang,Fengfeng Peng,Dandan Luo et al.
Bocheng Liang et al.
Background: Accurate segmentation of critical anatomical structures in fetal four-chamber view images is essential for the early detection of congenital heart defects. Current prenatal screening methods rely on manual mea...
al-BERT: a semi-supervised denoising technique for disease prediction [0.03%]
半监督去噪技术在疾病预测中的应用：al-BERT
Yun-Chien Tseng,Chuan-Wei Kuo,Wen-Chih Peng et al.
Yun-Chien Tseng et al.
Background: Medical records are a valuable source for understanding patient health conditions. Doctors often use these records to assess health without solely depending on time-consuming and complex examinations. However,...
BarlowTwins-CXR: enhancing chest X-ray abnormality localization in heterogeneous data with cross-domain self-supervised learning [0.03%]
利用跨领域自监督学习在异构数据中增强胸部X光片异常定位
Haoyue Sheng,Linrui Ma,Jean-François Samson et al.
Haoyue Sheng et al.
Background: Chest X-ray imaging based abnormality localization, essential in diagnosing various diseases, faces significant clinical challenges due to complex interpretations and the growing workload of radiologists. Whil...
Evaluation of activities of daily living using an electronic version of the Longshi Scale in patients with stroke: reliability, consistency, and preference [0.03%]
长石量表电子版在卒中患者日常生活活动评估中的信度、一致性及适用性分析
Kaiwen Xue,Weihao Li,Fang Liu et al.
Kaiwen Xue et al.
Background: The Longshi Scale is a pictorial assessment tool for evaluating activities of daily living (ADL) in patients with stroke. The paper-based version presents challenges; thus, the WeChat version was created to en...
Optimizing deep learning-based segmentation of densely packed cells using cell surface markers [0.03%]
基于细胞表面标记物优化密集细胞群的深度学习分割方法
Sunwoo Han,Khamsone Phasouk,Jia Zhu et al.
Sunwoo Han et al.
Background: Spatial molecular profiling depends on accurate cell segmentation. Identification and quantitation of individual cells in dense tissues, e.g. highly inflamed tissue caused by viral infection or immune reaction...
Prediction of carbapenem-resistant gram-negative bacterial bloodstream infection in intensive care unit based on machine learning [0.03%]
基于机器学习的重症监护室碳青霉烯类耐药革兰阴性细菌血流感染预测模型研究
Qiqiang Liang,Shuo Ding,Juan Chen et al.
Qiqiang Liang et al.
Background: Predicting whether Carbapenem-Resistant Gram-Negative Bacterial (CRGNB) cause bloodstream infection when giving advice may guide the use of antibiotics because it takes 2-5 days conventionally to return the re...
Natalia García Sánchez,Esther Ugarte Carro,Lucía Prieto-Santamaría et al.
Natalia García Sánchez et al.
Motivation: Drug repurposing speeds up the development of new treatments, being less costly, risky, and time consuming than de novo drug discovery. There are numerous biological elements that contribute to the development...
Colorectal cancer health and care quality indicators in a federated setting using the Personal Health Train [0.03%]
基于Personal Health Train的联合学习 colorectal癌健康和护理质量指标
Ananya Choudhury,Esther Janssen,Bart C Bongers et al.
Ananya Choudhury et al.
Objective: Hospitals and healthcare providers should assess and compare the quality of care given to patients and based on this improve the care. In the Netherlands, hospitals provide data to national quality registries, ...
Improved nonparametric survival prediction using CoxPH, Random Survival Forest & DeepHit Neural Network [0.03%]
基于Cox风险模型、随机森林及DeepHit神经网络的生存预测改进方法
Naseem Asghar,Umair Khalil,Basheer Ahmad et al.
Naseem Asghar et al.
In recent times, time-to-event data such as time to failure or death is routinely collected alongside high-throughput covariates. These high-dimensional bioinformatics data often challenge classical survival models, which are either infeasi...
Machine learning-empowered sleep staging classification using multi-modality signals [0.03%]
基于多模态信号的机器学习赋能睡眠分期分类方法
Santosh Kumar Satapathy,Biswajit Brahma,Baidyanath Panda et al.
Santosh Kumar Satapathy et al.
The goal is to enhance an automated sleep staging system's performance by leveraging the diverse signals captured through multi-modal polysomnography recordings. Three modalities of PSG signals, namely electroencephalogram (EEG), electroocu...