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For Data Science for Healthcare and Clinical Informatics Students

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A roadmap to using randomization in clinical trials
Interpretable instance disease prediction based on causal feature selection and effect analysis
DECE: DecisionExplorerwithCounterfactualExplanationsforMachineLearningModelsFuruiCheng,
Multi-level pooling encoder–decoder convolution neural network for MRI reconstruction
Added-value of mosquito vector breeding sites from street view images in the risk mapping of dengue incidence in Thailand
Large language models encode clinical knowledge

 

 

For Clinical/Medical Epidemiology Students

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A “Do No Harm” Novel Safety Checklist and Research Approach to Determine Whether to Launch an Artificial Intelligence–Based Medical Technology: Introducing the Biological-Psychological, Economic, and Social (BPES) Framework
APPRAISE-AI Tool for Quantitative Evaluation of AI Studies for Clinical Decision Support
Alternative approaches for confounding adjustment in  observational studies using weighting based on the propensity score: a primer for practitioners
Multi-state network meta-analysis of progression and survival data
Meta-epidemiological review identified variable reporting and handling of time-toevent analyses in publications of trials included in meta-analyses of systematic reviews
SuperMICE: An Ensemble Machine Learning Approach to Multiple Imputation by Chained Equations
Guidelines for Reporting Outcomes in Trial Protocols The SPIRIT-Outcomes 2022 Extension
Guidelines for Reporting Outcomes in Trial Reports The CONSORT-Outcomes 2022 Extension
Individualized dynamic prediction of survival with the presence of intermediate events
Representation learning for clinical time series prediction tasks in electronic health records

Estimates of years of life lost depended on the method used: tutorial and comparative investigation

Joint modelling of endpoints can be used to answer various research questions in randomized clinical trials
Believing in black boxes: machine learning for healthcare does not need explainability to be evidence-based
Forecasting of Patient-Specific Kidney Transplant Function With a Sequence-to-Sequence Deep Learning Model
Effect Decomposition in the Presence of Treatment-induced Confounding A Regression-with-residuals Approach
Quality assessment practice in systematic reviews of mediationstudies: results from an overview of systematic reviews
Raising the bar for using surrogate endpoints in drug regulation and health technology assessment
Should regulatory authorities approve drugs based on surrogate endpoints?
A Guideline for Reporting Mediation Analyses of Randomized Trials and Observational Studies
Deep Learning-based Propensity Scores for Confounding Control in Comparative Effectiveness Research
Incremental Benefits of Machine Learning: When DoWe Need a BetterMousetrap?
Prediction Models : Development, Evaluation,and Clinical Application
Equity and Artificial Intelligence in Surgical Care
Minimal important difference estimates for patient-reported outcomes: Asystematic survey
Logistic regression and machine learning predicted patient mortality fromlarge sets of diagnosis codes comparably
Questionable utility of the relative risk in clinical research: A call for change to practice
The statistical significance of randomized controlled trial results isfrequently fragile: a case for a Fragility Index
Why Most Discovered True Associations Are Inflated
Beyond Power Calculations: Assessing Type S (Sign) and Type M (Magnitude) Errors
Evaluating large-scale propensity score performance through real-world and synthetic data experiments
Handling Missing Values in Interrupted Time Series Analysis of Longitudinal Individual-Level Data
Development and Validation of a Natural Language Processing Tool to Generate the CONSORT Reporting Checklist for Randomized Clinical Trials
Nonparametric Statistical Analysis
Machine learning and AI research for Patient Benefit: 20 Critical Questions on Transparency, Replicability, Ethics and Effectiveness
A comparison of arm-based and contrast-based models fornetwork meta-analysis
Internal and External Validation of a Machine Learning Risk Score for Acute Kidney Injury
Effect of a Machine Learning–Derived Early Warning System for Intraoperative Hypotension vs Standard Care on Depth and Duration of Intraoperative Hypotension During Elective Noncardiac Surgery The HYPE Randomized Clinical Trial
Assessment of Electronic Health Record Search Patterns and Practices by Practitioners in a Large Integrated Health Care System
Estimates of Overall Survival in Patients With Cancer Receiving Different Treatment Regimens
Prospective and External Evaluation of a Machine Learning Model to Predict In-Hospital Mortality of Adults at Time of Admission
Assessment Causality in Associations Between Serum Uric Acid and Risk of Schizophrenia A Two-Sample Bidirectional Mendelian Randomization Study

Development and Validation of a Deep Learning Algorithm for Detection of Diabetic Retinopathy in Retinal Fundus Photographs

Consistent Estimation in Mendelian Randomization with Some Invalid Instruments Using a Weighted Median Estimator
Combining information on multiple instrumental variables in Mendelian randomization: comparison of allele score and summarized data methods
Using multiple genetic variants as instrumental variables for modifiable risk factors
Assessing the accuracy of machine-assisted abstract screening with DistillerAI- a user study
Extending PubMed searches to ClinicalTrials.gov through a machine learning approach for systematic reviews
Performance and usability of machine learning for screening in systematic reviews- a comparative evaluation of three tools
Screening PubMed abstracts- is class imbalance always a challenge to machine learning
5-11-2014 Adaptive list sequential sampling method for population-based observational studies  
A counterfactual approach to bias and effect modification in terms of response types
Longitudinal-handling dropout
Longitudinal-infomation based sample size
Meta-analysis-multivariate and meta-regression
Meta-epidemiologic analysis indicates that MEDLINE searches are sufficient for diagnostic test accuracy systematic review
Predictive distributions were developed for the extent of heterogeneity in meta-analyses of continuous  outcome data
Using multiple imputation to deal with missing data and attrition in longitudinal studies with repeated measures of patient-reported outcomes
Causal inference as an emerging statistical approach in neurology: an example for epilepsy in the elderly
A design-by-treatment interaction model for network meta-analysis with random inconsistency effects
Evaluation of inconsistency in networks of interventions
GRADE guidelines: 6
A GRADE Working Group approach for rating the quality of treatment effect estimates from network meta-analysis
Multiple Criteria Decision Analysis for Health Technology Assessment
Nice DSU Technical Support Document 7: Evidence Synthesis of Treatment Efficacy in Decision Making: A Reviewer's Checklist
Between-study heterogeneity and inconsistency in mixed treatment comparisons - stroke prevention in non-rheumatic atrial fibrillation
 Combining randomised and non-randomised evidence in network meta-analyis  
Multiple-treatments meta-analyis demonstrates covariates should be considered
Network meta-analysis models to account for variability in treatment definitions - application to dose effects
Clinical epidemiology in the era of big data: new opportunities, familiar challenges
An analysis of protocols and publications suggested that most discontinuations of clinical trials were not based on preplanned interim analyses or stopping rules
Thrombolysis for Pulmonary Embolism - A Meta-analysis
Applying Net Benefit framework for assessing cost-effectiveness of interventions to wards universal health coverage
Comparing multiple competing interventions in the absence of randomized trials using clinical risk-benefit analysis
Evidence based prescribing- combing NMA with multicriteria decision analysis to choose among multi drug
Example article ProMise study - INB
How to estimate cost-effectiveness acceptability curves INB alongside RCTs
INB-COMER MA of cost-effectiveness
Net Health Benefits
A protocol for cluster RCT
Cluster RCT for reduction of alcohol consumption A study protocol
Community-based participatory research from the margin to mainstream
Design and analysis of community trials
Reconsidering community-based health promotion
Selected methodological issues in evaluating community-based health promotion programannurev.pu.13.050192
Statistical models appropriate for designs often used in group-RCTs
A comparison of existing methods for multiple imputation in individual participant data meta-analysis
Predictive Big Data Analytics: A Study of Parkinson's Disease Using Large, Complex, Heterogeneous, Incongruent, Multi-Sourse and Incomplete Observations
A novel case-control subsampling approach for rapid model exploration of large clustered binary data
A practical guide to big data research in psychology
Concurrence of big data analytics and healthcare_a systematic review
Epidemiology in the Era of Big Data
Epidemiology in wonderland
Ethics big data and computing in epidemiology and public health
Finding the evidence in real-world evidence moving from data to information to knowledge
How to responsibly acknowledge research work in the era of big data and biobanks
Individual privacy versus public good protecting confidentiality inhealth research
SLBD_new
Statistical methods and computing for big data
Supplementalmaterials for A practical guide to big data research in psychology
Ten years of research change using Google trends
Thailand's universal coverage
Use of the medicare database in epidemiologic and health services research
Validation of algorithms to determine incidence of hirschsprung disease in Ontorio
Diclofenac use and cardiovascular risks: series of nationwide cohort studies
Computer-aided diagnosis of glaucoma using fundus images: A review
Overachieving Municipalities in Public Health: A Machine-learning Approach
Potential Biases in Machine Learning Algorithms Using Electronic Health Record Data
Prediction of paroxysmal Atrial Fibrillation: A machine learning based approach using combined feature vector and mixture of expert classification on HRV signal
Validating a Machine Learning Algorithm to Predict 30-Day Re-Admissions in Patients With Heart Failure: Protocol for a
Prospective Cohort Study
Comparison of Machine Learning Approaches Toward Assessing the Risk of Developing Cardiovascular Disease as a Long-Term Diabetes Complication
Development of Big Data Predictive Analytics Model for Disease
Using predictive analytics and big data to optimize
A model for meta-analysis of correlated binary outcomes: The case of split-body interventions
Treatment selection bias for chemotherapy persists in colorectal cancer patient cohort studies even in comprehensive propensity score analyses
Adaptive enrichment designs for confirmatory trials
Meta-analysis for the comparison of two diagnostic tests to a common gold standard: A generalized linear mixed model approach
Analysis of Observational Studies in the Presence of Treatment Selection Bias: Effects of Invasive Cardiac Management on AMI Survival Using Propensity Score and Instrumental Variable Methods
Estimating Treatment Effects Using Observational Data
Real- world data: towards achieving the achievable in cancer care
The cohort multiple randomized controlled trial design: a valid and efficient alternative to pragmatic trials?
The Trials within Cohorts design faced methodological advantages and disadvantages in the exercise oncology setting

 

 
Department of Clinical Epidemiology and Biostatistics