71 citations · 308 across the 21 of their papers we have counts for
21 papers
Benchmarking Classification Tasks of Chest X-ray AI Across Multinational Public and Private Datasets: a retrospective diagnostic accuracy study
Qinmei Xu, Yiheng Li, Wenya Zhao +22
Chest X-ray (CXR) AI models are increasingly proposed for triage, screening, and rule-out, where the operating point is fixed to miss few abnormalities. Most evaluations instead re…
Differences between Two Maximal Principal Strain Rate Calculation Schemes in Traumatic Brain Analysis with in-vivo and in-silico Datasets
Xianghao Zhan, Zhou Zhou, Yuzhe Liu +5
Brain deformation caused by a head impact leads to traumatic brain injury (TBI). The maximum principal strain (MPS) was used to measure the extent of brain deformation and predict…
Identification of head impact locations, speeds, and force based on head kinematics
Xianghao Zhan, Yuzhe Liu, Nicholas J. Cecchi +5
Objective: Head impact information including impact directions, speeds and force are important to study traumatic brain injury, design and evaluate protective gears. This study pre…
Reliability-based cleaning of noisy training labels with inductive conformal prediction in multi-modal biomedical data mining
Xianghao Zhan, Qinmei Xu, Yuanning Zheng +2
Accurately labeling biomedical data presents a challenge. Traditional semi-supervised learning methods often under-utilize available unlabeled data. To address this, we propose a n…
Toward more accurate and generalizable brain deformation estimators for traumatic brain injury detection with unsupervised domain adaptation
Xianghao Zhan, Jiawei Sun, Yuzhe Liu +5
Machine learning head models (MLHMs) are developed to estimate brain deformation for early detection of traumatic brain injury (TBI). However, the overfitting to simulated impacts…
Denoising instrumented mouthguard measurements of head impact kinematics with a convolutional neural network
Xianghao Zhan, Yuzhe Liu, Nicholas J. Cecchi +6
Wearable sensors for measuring head kinematics can be noisy due to imperfect interfaces with the body. Mouthguards are used to measure head kinematics during impacts in traumatic b…
Padded Helmet Shell Covers in American Football: A Comprehensive Laboratory Evaluation with Preliminary On-Field Findings
Nicholas J. Cecchi, Ashlyn A. Callan, Landon P. Watson +8
Protective headgear effects measured in the laboratory may not always translate to the field. In this study, we evaluated the impact attenuation capabilities of a commercially avai…
Filter Drug-induced Liver Injury Literature with Natural Language Processing and Ensemble Learning
Xianghao Zhan, Fanjin Wang, Olivier Gevaert
Drug-induced liver injury (DILI) describes the adverse effects of drugs that damage liver. Life-threatening results including liver failure or death were also reported in severe DI…
Data-driven decomposition of brain dynamics with principal component analysis in different types of head impacts
Xianghao Zhan, Yuzhe Liu, Nicholas J. Cecchi +4
Strain and strain rate are effective traumatic brain injury predictors. Kinematics-based models estimating these metrics suffer from significant different distributions of both kin…
Unsupervised cross-user adaptation in taste sensation recognition based on surface electromyography with conformal prediction and domain regularized component analysis
Hengyang Wang, Xianghao Zhan, Li Liu +5
Human taste sensation can be qualitatively described with surface electromyography. However, the pattern recognition models trained on one subject (the source domain) do not genera…
Rapidly and accurately estimating brain strain and strain rate across head impact types with transfer learning and data fusion
Xianghao Zhan, Yuzhe Liu, Nicholas J. Cecchi +4
Brain strain and strain rate are effective in predicting traumatic brain injury (TBI) caused by head impacts. However, state-of-the-art finite element modeling (FEM) demands consid…
Kinematics clustering enables head impact subtyping for better traumatic brain injury prediction
Xianghao Zhan, Yiheng Li, Yuzhe Liu +5
Traumatic brain injury can be caused by various types of head impacts. However, due to different kinematic characteristics, many brain injury risk estimation models are not general…
CPSC: Conformal prediction with shrunken centroids for efficient prediction reliability quantification and data augmentation, a case in alternative herbal medicine classification with electronic nose
Li Liu, Xianghao Zhan, Xikai Yang +6
In machine learning applications, the reliability of predictions is significant for assisted decision and risk control. As an effective framework to quantify the prediction reliabi…
Machine-learning-based head impact subtyping based on the spectral densities of the measurable head kinematics
Xianghao Zhan, Yiheng Li, Yuzhe Liu +11
Objective: Traumatic brain injury can be caused by head impacts, but many brain injury risk estimation models are not equally accurate across the variety of impacts that patients m…
Classifying herbal medicine origins by temporal and spectral data mining of electronic nose
Li Liu, Xianghao Zhan, Ziheng Duan +6
The origins of herbal medicines are important for their treatment effect, which could be potentially distinguished by electronic nose system. As the odor fingerprint of herbal medi…
Time Window of Head Impact Kinematics Measurement for Calculation of Brain Strain and Strain Rate in American Football
Yuzhe Liu, August G. Domel, Nicholas J. Cecchi +8
Wearable devices have been shown to effectively measure the head movement during impacts in sports like American football. When a head impact occurs, the device is triggered to col…
Predictive Factors of Kinematics in Traumatic Brain Injury from Head Impacts Based on Statistical Interpretation
Xianghao Zhan, Yiheng Li, Yuzhe Liu +12
Brain tissue deformation resulting from head impacts is primarily caused by rotation and can lead to traumatic brain injury. To quantify brain injury risk based on measurements of…
Boost AI Power: Data Augmentation Strategies with unlabelled Data and Conformal Prediction, a Case in Alternative Herbal Medicine Discrimination with Electronic Nose
Li Liu, Xianghao Zhan, Rumeng Wu +7
Electronic nose has been proven to be effective in alternative herbal medicine classification, but due to the nature of supervised learning, previous research heavily relies on the…
Theoretical and numerical analysis for angular acceleration being determinant of brain strain in mTBI
Yuzhe Liu, Xianghao Zhan, August G. Domel +7
Mild traumatic brain injury (mTBI, also known as concussion) caused by the head impact is a crucial global public health problem, but the physics of mTBI is still unclear. During t…
Relationship between brain injury criteria and brain strain across different types of head impacts can be different
Xianghao Zhan, Yiheng Li, Yuzhe Liu +10
Multiple brain injury criteria (BIC) are developed to quickly quantify brain injury risks after head impacts. These BIC originated from different types of head impacts (e.g., sport…
Deep Learning Head Model for Real-time Estimation of Entire Brain Deformation in Concussion
Xianghao Zhan, Yuzhe Liu, Samuel J. Raymond +6
Objective: Many recent studies have suggested that brain deformation resulting from a head impact is linked to the corresponding clinical outcome, such as mild traumatic brain inju…