Area of research
Insect Science · Surgery
Research interest
Research focused on Metabolomics and Neurogenesis, with related work in Vitality, microRNA, Inference. Notable publications include 'Neuroblast senescence in the aged brain augments natural killer cell cytotoxicity leading to impaired neurogenesis and cognition', 'Vitality and wound-age estimation in forensic pathology: review and future prospects', and 'Combined metabolomics and machine learning algorithms to explore metabolic biomarkers for diagnosis of acute myocardial ischemia'.
PAI-1 regulates extracellular matrix remodeling and alters fibroblast profibrotic ability in skeletal muscle repair
Artificial intelligence in forensic pathology: Multi-organ postmortem pathomics for estimating postmortem interval
Etiology-Agnostic Diagnosis of Early Myocardial Ischemia via AI-Driven Label-Free Spectral Histopathology
Novel Strategy for Human Deep Vein Thrombosis Diagnosis Based on Metabolomics and Stacking Machine Learning
Development of a screening system of gene sets for estimating the time of early skeletal muscle injury based on second-generation sequencing technology
The Impact of Cardiovascular Disease Gene Polymorphism and Interaction with Homocysteine on Deep Vein Thrombosis
Multi-omics integration strategy in the post-mortem interval of forensic science
Exploring postmortem succession of rat intestinal microbiome for PMI based on machine learning algorithms and potential use for humans
GPR65 as a potential immune checkpoint regulates the immune microenvironment according to pan-cancer analysis
Forensic identification of sudden cardiac death: a new approach combining metabolomics and machine learning
Novel Prediction Method Applied to Wound Age Estimation: Developing a Stacking Ensemble Model to Improve Predictive Performance Based on Multi-mRNA
Combined metabolomics and tandem machine-learning models for wound age estimation: a novel analytical strategy
Combining with lab-on-chip technology and multi-organ fusion strategy to estimate post-mortem interval of rat
Novel ratio-expressions of genes enables estimation of wound age in contused skeletal muscle
Postmortem Interval Estimation Using Protein Chip Technology Combined with Multivariate Analysis Methods.
Combined metabolomics and machine learning algorithms to explore metabolic biomarkers for diagnosis of acute myocardial ischemia
A novel method for determining postmortem interval based on the metabolomics of multiple organs combined with ensemble learning techniques
Wound age estimation based on next-generation sequencing: Fitting the optimal index system using machine learning
Comparison of Medical Dispute Resolution Mechanisms in China and Abroad.
Comparison among Four Deep Learning Image Classification Algorithms in AI-based Diatom Test.
Investigating Transcriptional Dynamics Changes and Time-Dependent Marker Gene Expression in the Early Period After Skeletal Muscle Injury in Rats
Insight into molecular profile changes after skeletal muscle contusion using microarray and bioinformatics analyses
Estimating Postmortem Interval Using Intestinal Microbiota Diversity Based on 16S rRNA High-throughput Sequencing Technology.
Estimating the time of skeletal muscle contusion based on the spatial distribution of neutrophils: a practical approach to forensic problems
Neuroblast senescence in the aged brain augments natural killer cell cytotoxicity leading to impaired neurogenesis and cognition
Analysis of sensitivity and specificity: precise recognition of neutrophils during regeneration of contused skeletal muscle in rats
Novel insights into wound age estimation: combined with “up, no change, or down” system and cosine similarity in python environment
Investigating the new orientation of wound age estimation in forensic medicine based on biological omics data combined with artificial intelligence algorithms
Characterization and postmortem diagnosis of fatal heatstroke using Attenuated Total Reflectance Fourier transform infrared spectroscopy combined with chemometrics
Temporal expression of wound healing–related genes inform wound age estimation in rats after a skeletal muscle contusion: a multivariate statistical model analysis