High-resolution 3D flow reconstruction of cerebrospinal fluid microcirculation using physics-informed neural network: Conceptualization and application to a large animal model [0.03%]
基于物理知识的神经网络的高分辨率脑脊液微循环三维流场重构：概念及大动物模型应用研究
Mark Epshtein,Tirosh Mekler,Mohammed Salman Shazeeb et al.
Mark Epshtein et al.
In this study, we present a novel Physics-Informed Neural Network (PINN) framework that reconstructs 3D flows using planar velocity projections from arbitrarily oriented planes. The method is designed for the reconstruction of low-Reynolds-...
Uncertainty‑aware sepsis survival prediction using conformal XGBoost on minimal clinical features under Sepsis‑3 criteria [0.03%]
基于Sepsis-3标准的最小临床特征下使用符合XGBoost进行不确定性感知的脓毒症生存预测
Samuel John Parreño
Samuel John Parreño
Background and objective: Sepsis remains a major cause of in-hospital mortality, but many prognostic models require extensive clinical data. This study evaluated whether a minimal-feature XGBoost model combined with induc...
From 2D to 3D: Automated ultrasound segmentation and cross-sectional validation in murine tumor models [0.03%]
从2D到3D：自动超声分割和小鼠肿瘤模型的横截面验证
Weronika Smolak-Dyżewska,Jerzy Bazak,Wiktoria Brandys et al.
Weronika Smolak-Dyżewska et al.
Background and objective: Ultrasound (US) is a widely used method for non-invasive tumor monitoring. Semantic segmentation of tumors in US imagery is a necessary step to reconstruct 3D geometry of a region of interest (RO...
A novel qVGG-4 model for optimizing a parameterized quantum circuit in a quantum-IoT-based brain tumor detection and monitoring system [0.03%]
一种新型qVGG-4模型在基于量子物联网的脑肿瘤检测和监测系统中的参数化量子电路优化中应用
Md Taimur Ahad,Bo Song,Yan Li
Md Taimur Ahad
Background: Since brain tumors (BTs) require early detection for timely and effective treatment planning, this study presents two quantum deep learning (Q-DL) approaches: a quantum Convolutional Neural Network (CNN) and a...
Neural estimates of language comprehension of sentences with selected action verbs in a non-literal context in the Polish language studied by permutation cluster-based analysis and decoding of the event-related potentials [0.03%]
基于置换聚类分析和事件相关电位解码的波兰语非字面情境中动词句子语言理解的神经估计
Karina Maciejewska,Kamil Wałczyk,Tomasz Nowak
Karina Maciejewska
Background: This work examines how the human brain processes mental metaphors in Polish verbal phraseologisms (a fixed, non-compositional combination of at least two elements that conveys a single meaning distinct from it...
PPG-basis: A python-based toolbox for fast photoplethysmogram decomposition and reconstruction [0.03%]
基于Python的快速光电容积描记信号分解与重建工具箱PPG-basis
Arjun Putcha,Rachit Keyal,Luke Piasecki et al.
Arjun Putcha et al.
Background & objective: Photoplethysmogram (PPG) data are commonly used for critical biometric extractions, such as heart rate and blood oxygenation. However, PPG data contains valuable information on other metrics, such ...
IML-UNet: A brain-inspired spatiotemporal collaborative encoding method for medical image sequence registration [0.03%]
一种受脑启发的时空协作编码医学图像序列配准方法
Xinyu Liu,Xing Chen,Zhijia Wang et al.
Xinyu Liu et al.
Background and objective: Deformable medical image registration is important for radiotherapy planning, respiratory motion analysis, and organ function assessment. In medical image sequences such as 4D CT, organ motion in...
Time-resolved aortic 3D shape reconstruction from a limited number of cine 2D MRI slices [0.03%]
基于有限个心电图二维MRI图像的主动脉三维形状的时间分辨重建
Gloria Wolkerstorfer,Stefano Buoso,Rabea Schlenker et al.
Gloria Wolkerstorfer et al.
Background and objective: To assess the feasibility and accuracy of reconstructing time-resolved, three-dimensional, subject-specific aortic geometries from a limited number of standard cine 2D magnetic resonance imaging ...
Radiomic feature-based classification of BI-RADS 4/5 breast lesions on contrast-enhanced mammography [0.03%]
基于BI-RADS 4/5类乳腺病变造影乳腺X线摄影的影像组学特征分类研究
Wiktoria Błędzińska,Jakub Pałachniak,Mateusz Winder et al.
Wiktoria Błędzińska et al.
Background and objective: Differentiating benign from malignant BI-RADS 4/5 lesions, particularly architectural distortions, remains challenging. We investigated whether radiomics from contrast-enhanced mammography (low-e...
Hybrid learning/numerical framework for fast and robust electric field simulation in irreversible electroporation [0.03%]
用于不可逆电穿孔的快速可靠的电场模拟的混合学习/数值框架
Kylian Desier,Olivier Sutter,Luc Lafitte et al.
Kylian Desier et al.
Objective: Irreversible electroporation (IRE) represents a promising non-thermal ablation modality for the treatment of deep-seated tumors. However, its clinical efficacy is critically dependent on the accurate, patient-s...