Ji Zhu
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View article: Reprogramming cellular senescence and aging clocks for advanced cancer immunotherapy
Reprogramming cellular senescence and aging clocks for advanced cancer immunotherapy Open
View article: Interpretable Network-assisted Random Forest+
Interpretable Network-assisted Random Forest+ Open
Machine learning algorithms often assume that training samples are independent. When data points are connected by a network, the induced dependency between samples is both a challenge, reducing effective sample size, and an opportunity to …
View article: Modeling Non-Uniform Hypergraphs Using Determinantal Point Processes
Modeling Non-Uniform Hypergraphs Using Determinantal Point Processes Open
Most statistical models for networks focus on pairwise interactions between nodes. However, many real-world networks involve higher-order interactions among multiple nodes, such as co-authors collaborating on a paper. Hypergraphs provide a…
View article: Publisher Correction to: Quantifying intra-urban socio-economic and environmental vulnerability to extreme heat events in Johannesburg, South Africa
Publisher Correction to: Quantifying intra-urban socio-economic and environmental vulnerability to extreme heat events in Johannesburg, South Africa Open
View article: Towards Concise and Adaptive Thinking in Large Reasoning Models: A Survey
Towards Concise and Adaptive Thinking in Large Reasoning Models: A Survey Open
Large reasoning models (LRMs) like OpenAI o1 and DeepSeek R1 have demonstrated impressive performance on complex reasoning tasks like mathematics and programming with long Chain-of-Thought (CoT) reasoning sequences (slow-thinking), compare…
View article: Application of spatial and single-cell omics in tumor immunotherapy biomarkers
Application of spatial and single-cell omics in tumor immunotherapy biomarkers Open
View article: Key predictors of maternal mild depression and anxiety in low resource settings: A machine learning approach
Key predictors of maternal mild depression and anxiety in low resource settings: A machine learning approach Open
Background Maternal mental health (MMH) disorders, particularly depression and anxiety, are major public health concerns in low- and middle-income countries (LMICs). In sub-Saharan Africa (SSA), their prevalence remains alarmingly high, ye…
View article: Modeling Hypergraphs with Diversity and Heterogeneous Popularity
Modeling Hypergraphs with Diversity and Heterogeneous Popularity Open
While relations among individuals make an important part of data with scientific and business interests, existing statistical modeling of relational data has mainly been focusing on dyadic relations, i.e., those between two individuals. Th…
View article: English Publicity of Chinese Modern Pastoral Poetry—A Case Study of Zhejiang
English Publicity of Chinese Modern Pastoral Poetry—A Case Study of Zhejiang Open
Chinese pastoral poetry with its distinctive essence and profound research value, stands as a cultural gem cherished by people worldwide. The publicity of this poetic genre is pivotal for its evolution in contemporary times. This study, ce…
View article: Flexible Modeling of Information Diffusion on Networks with Statistical Guarantees
Flexible Modeling of Information Diffusion on Networks with Statistical Guarantees Open
Modeling information spread through a network is one of the key problems of network analysis, with applications in a wide array of areas such as marketing and public health. Most approaches assume that the spread is governed by some probab…
View article: Mesoscale two-sample testing for network data
Mesoscale two-sample testing for network data Open
Networks arise naturally in many scientific fields as a representation of pairwise connections. Statistical network analysis has most often considered a single large network, but it is common in a number of applications, for example, neuro…
View article: GSON: A Group-based Social Navigation Framework with Large Multimodal Model
GSON: A Group-based Social Navigation Framework with Large Multimodal Model Open
With the increasing presence of service robots and autonomous vehicles in human environments, navigation systems need to evolve beyond simple destination reach to incorporate social awareness. This paper introduces GSON, a novel group-base…
View article: Computing Wasserstein Barycenter via operator splitting: the method of averaged marginals
Computing Wasserstein Barycenter via operator splitting: the method of averaged marginals Open
The Wasserstein barycenter (WB) is an important tool for summarizing sets of probability measures. It finds applications in applied probability, clustering, image processing, etc. When the measures' supports are finite, computing a (balanc…
View article: Prediction of Gastrointestinal Tract Cancers Using Longitudinal Electronic Health Record Data
Prediction of Gastrointestinal Tract Cancers Using Longitudinal Electronic Health Record Data Open
Background: Luminal gastrointestinal (GI) tract cancers, including esophageal, gastric, small bowel, colorectal, and anal cancers, are often diagnosed at late stages. These tumors can cause gradual GI bleeding, which may be unrecognized bu…
View article: Greater geographic sharing and heart transplantation waitlist outcomes following the 2018 heart allocation policy
Greater geographic sharing and heart transplantation waitlist outcomes following the 2018 heart allocation policy Open
View article: Different gut microbiota in U.S. formula-fed infants consuming a meat vs. dairy-based complementary foods: A randomized controlled trial
Different gut microbiota in U.S. formula-fed infants consuming a meat vs. dairy-based complementary foods: A randomized controlled trial Open
Objective This project aimed to evaluate the impact of meat- vs. dairy-based complementary foods on gut microbiota and whether it relates to growth. Design Full-term, formula-fed infants were recruited from the metro Denver area (Colorado,…
View article: COVID-19 vaccine hesitancy among non-refugees and refugees in Kenya
COVID-19 vaccine hesitancy among non-refugees and refugees in Kenya Open
Factors associated with COVID-19 vaccine hesitancy (which we define as refusal to be vaccinated when asked, resulting in delayed or non- vaccination) are poorly studied in sub-Saharan Africa and among refugees, particularly in Kenya. Using…
View article: Artificial intelligence and machine learning for early detection and diagnosis of colorectal cancer in sub-Saharan Africa
Artificial intelligence and machine learning for early detection and diagnosis of colorectal cancer in sub-Saharan Africa Open
View article: Reinforcement learning evaluation of treatment policies for patients with hepatitis C virus
Reinforcement learning evaluation of treatment policies for patients with hepatitis C virus Open
View article: Bayesian Inferences on Neural Activity in EEG-Based Brain-Computer Interface
Bayesian Inferences on Neural Activity in EEG-Based Brain-Computer Interface Open
A brain-computer interface (BCI) is a system that translates brain activity into commands to operate technology. A common design for an electroencephalogram (EEG) BCI relies on the classification of the P300 event-related potential (ERP), …
View article: Adapted time-varying covariates Cox model for predicting future cirrhosis development performs well in a large hepatitis C cohort
Adapted time-varying covariates Cox model for predicting future cirrhosis development performs well in a large hepatitis C cohort Open
View article: A structured brain‐wide and genome‐wide association study using ADNI PET images
A structured brain‐wide and genome‐wide association study using ADNI PET images Open
Background Detecting association signals between the brain and the genome using ultrahigh‐dimensional PET neuroimaging scans and GWAS SNP data Method A multi‐stage variable selection method is introduced for detecting association signals i…
View article: Replicating prediction algorithms for hospitalization and corticosteroid use in patients with inflammatory bowel disease
Replicating prediction algorithms for hospitalization and corticosteroid use in patients with inflammatory bowel disease Open
Introduction Previous work had shown that machine learning models can predict inflammatory bowel disease (IBD)-related hospitalizations and outpatient corticosteroid use based on patient demographic and laboratory data in a cohort of Unite…
View article: Optimizing hepatitis B virus screening in the United States using a simple demographics‐based model
Optimizing hepatitis B virus screening in the United States using a simple demographics‐based model Open
Background and Aims Chronic hepatitis B (CHB) affects >290 million persons globally, and only 10% have been diagnosed, presenting a severe gap that must be addressed. We developed logistic regression (LR) and machine learning (ML; random f…
View article: Stratified Cox models with time‐varying effects for national kidney transplant patients: A new blockwise steepest ascent method
Stratified Cox models with time‐varying effects for national kidney transplant patients: A new blockwise steepest ascent method Open
Analyzing the national transplant database, which contains about 300,000 kidney transplant patients treated in over 290 transplant centers, may guide the disease management and inform the policy of kidney transplantation. Cox models strati…
View article: The Use of Readily Available Longitudinal Data to Predict the Likelihood of Surgery in Crohn Disease
The Use of Readily Available Longitudinal Data to Predict the Likelihood of Surgery in Crohn Disease Open
Background Although imaging, endoscopy, and inflammatory biomarkers are associated with future Crohn disease (CD) outcomes, common laboratory studies may also provide prognostic opportunities. We evaluated machine learning models incorpora…
View article: A structured brain‐wide and genome‐wide association study using ADNI PET images
A structured brain‐wide and genome‐wide association study using ADNI PET images Open
A multistage variable selection method is introduced for detecting association signals in structured brain‐wide and genome‐wide association studies (brain‐GWAS). Compared to conventional methods that link one voxel to one single nucleotide…
View article: Clinical applications of artificial intelligence and machine learning‐based methods in inflammatory bowel disease
Clinical applications of artificial intelligence and machine learning‐based methods in inflammatory bowel disease Open
Our objective was to review and exemplify how selected applications of artificial intelligence (AI) might facilitate and improve inflammatory bowel disease (IBD) care and to identify gaps for future work in this field. IBD is highly comple…
View article: MuSP: A multistep screening procedure for sparse recovery
MuSP: A multistep screening procedure for sparse recovery Open
We propose a multistep screening procedure (MuSP) for the recovery of sparse linear models in high‐dimensional data. This method is based on a repeated small penalty strategy that quickly converges to an estimate within a few iterations. S…
View article: Limiting laws and consistent estimation criteria for fixed and diverging number of spiked eigenvalues
Limiting laws and consistent estimation criteria for fixed and diverging number of spiked eigenvalues Open
In this paper, we study limiting laws and consistent estimation criteria for the extreme eigenvalues in a spiked covariance model of dimension $p$. Firstly, for fixed $p$, we propose a generalized estimation criterion that can consistently…