ReHeartNet: Reconstruct Electrocardiogram From Photoplethysmography by Using Dense Connected Deep Learning Model [0.03%]
基于密集连接深度学习模型的心电图光电容积描记信号重建方法
Shuenn-Yuh Lee,Kai-Ze Lei,Ju-Yi Chen et al.
Shuenn-Yuh Lee et al.
Goal: To enable comfortable and non-invasive heart rhythm monitoring, this work aims to reconstruct electrocardiogram (ECG) signals from photoplethysmogram (PPG) signals, eliminating the need for multiple electrode attachments, which are of...
3D Engineered Biomimetic Platform for Characterization of Collective Invasion, Tumor Emboli Formation, and Lymphatic Dissemination [0.03%]
一种三维工程仿生平台用于表征集体侵袭、肿瘤栓子形成和淋巴扩散
Caroline Way,Ralph F Erdmann,Larisa Gearhart-Serna et al.
Caroline Way et al.
Goal: Emerging evidence in diverse tumor types establishes a link between lymphatic dissemination and collective tumor cell invasion. To simulate the biomechanical features of the tumor-lymphatic microenvironment, we developed a 3D tumor-ly...
Deep Learning-Based Decoding and Feature Visualization of Motor Imagery Speeds From EEG Signals [0.03%]
基于深度学习的脑电运动想象速度解码与特征可视化方法研究
Shogo Todoroki,Chatrin Phunruangsakao,Keisuke Goto et al.
Shogo Todoroki et al.
Objective: This study investigates the neurodynamics of motor imagery speed decoding using deep learning. Methods: The EEGConformer model was employed to analyze EEG signals and decode different speeds of imagined movements. Explainable art...
Performance Evaluation of a Novel Digital Flow-Imaging IV Infusion Device [0.03%]
一种新型数字灌注成像输液装置的性能评估研究
Robert D Butterfield,Nathaniel M Sims
Robert D Butterfield
Goal: Assess performance and potential use of a novel, servo-controlled, gravity-driven infusion device with FDA regulatory clearance obtained 3/1/2024(K242693). Introduction: "SAFEflowTM " (SF) using real time flow measurement and feedback...
Graph Attention Networks for Detecting Epilepsy From EEG Signals Using Accessible Hardware in Low-Resource Settings [0.03%]
基于图注意力网络的癫痫EEG信号检测方法及简易硬件实现方案
Szymon Mazurek,Stephen Moore,Alessandro Crimi
Szymon Mazurek
Goal: Epilepsy remains under-diagnosed in low-income countries due to scarce neurologists and costly diagnostic tools. We propose a graph-based deep learning framework to detect epilepsy from low-cost Electroencephalography (EEG) hardware, ...
YOLO-VML: An Improved Object Detection Model for Blastomeres and Pronuclei Localization in IoMT [0.03%]
用于IoMT中卵裂球和原核定位的改进型目标检测模型
Aiyun Shen,Chang Li,Jingwei Yang et al.
Aiyun Shen et al.
Goal: Blastomeres and pronuclei detection plays a crucial role in advancing research on embryo development and assisted reproductive technologies. However, due to the frequent overlapping of blastomeres and the pronuclei's small size, backg...
Assessing Alveolar Bone Volume Fraction in Dental Implantology Using 1.5 Tesla Magnetic Resonance Imaging: An Ex Vivo Cross-Sectional Study [0.03%]
基于1.5特斯拉磁共振成像的种植体周围骨体积分数评估：离体横断面研究
Jingting Yao,Shidong Xu,Isabela G G Choi et al.
Jingting Yao et al.
Objective: Oral implant procedures necessitate assessment of alveolar bone, a vital tooth-supporting structure. While micro-computed tomography (micro-CT) is the gold standard for bone volume fraction assessment for its high spatial resolut...
ArterialNet: Reconstructing Arterial Blood Pressure Waveform With Wearable Pulsatile Signals, a Cohort-Aware Approach [0.03%]
基于穿戴脉搏波的动脉血压波形重建算法及队列感知方法
Sicong Huang,Roozbeh Jafari,Bobak J Mortazavi
Sicong Huang
Goal: Continuous arterial blood pressure (ABP) waveform is invasive but essential for hemodynamic monitoring. Current non-invasive techniques reconstruct ABP waveforms with pulsatile signals but derived inaccurate systolic and diastolic blo...
Continuous, Contactless, and Multimodal Pain Assessment During Surgical Interventions [0.03%]
外科手术过程中的连续、无接触和多模态疼痛评估
Bianca Reichard,Mirco Fuchs,Kerstin Bode
Bianca Reichard
Goal: We introduce a continuous, multimodal pain classification technique that utilizes camera-based data conducted in clinical settings. Methods: We integrate facial Action Units (AUs) obtained from samples with sequential vital parameters...
Subtraction of Temporally Sequential Digital Mammograms: Enhancing the Detection and Classification of Malignant Masses in Breast Imaging [0.03%]
时间上连续的数字乳腺摄影相减法在乳腺影像中恶性肿块检测和分类中的应用研究
Kosmia Loizidou,Galateia Skouroumouni,Gabriella Savvidou et al.
Kosmia Loizidou et al.
Background: This study evaluates the performance of an automated method for detecting and classifying breast masses as Breast Imaging Reporting and Data System (BI-RADS) benign or biopsy-confirmed malignant using subtraction of temporally s...