Area of research
Artificial Intelligence · Health Informatics
Research interest
Research interests include Artificial Intelligence in Healthcare and Education, Machine Learning in Healthcare, COVID-19 diagnosis using AI, and Topic Modeling.
PROBAST+AI: an updated quality, risk of bias, and applicability assessment tool for prediction models using regression or artificial intelligence methods
Development and Validation of a Novel Deep Learning Model to Predict Pharmacologic Closure of Patent Ductus Arteriosus in Premature Infants
NeoCLIP: a self-supervised foundation model for the interpretation of neonatal radiographs
TRIPOD+AI statement: updated guidance for reporting clinical prediction models that use regression or machine learning methods: a Korean translation
TRIPOD+AI statement: updated guidance for reporting clinical prediction models that use regression or machine learning methods
To do no harm — and the most good — with AI in health care
Artificial Intelligence in Medicine
Assessment of ChatGPT success with specialty medical knowledge using anaesthesiology board examination practice questions
Performance of a Large Language Model on Practice Questions for the Neonatal Board Examination
Machine Learning and Statistics in Clinical Research Articles—Moving Past the False Dichotomy
Prediction of extubation failure among low birthweight neonates using machine learning
Reporting guideline for the early-stage clinical evaluation of decision support systems driven by artificial intelligence: DECIDE-AI
Artificial Intelligence Based on Machine Learning in Pharmacovigilance: A Scoping Review
The false hope of current approaches to explainable artificial intelligence in health care
Protocol for development of a reporting guideline (TRIPOD-AI) and risk of bias tool (PROBAST-AI) for diagnostic and prognostic prediction model studies based on artificial intelligence
Second opinion needed: communicating uncertainty in medical machine learning
Reporting guidelines for clinical trial reports for interventions involving artificial intelligence: the CONSORT-AI extension
Guidelines for clinical trial protocols for interventions involving artificial intelligence: the SPIRIT-AI extension
Time to reality check the promises of machine learning-powered precision medicine
Adversarial attacks on medical machine learning
Practical guidance on artificial intelligence for health-care data
Artificial intelligence in healthcare
Big Data and Machine Learning in Health Care
Postsurgical prescriptions for opioid naive patients and association with overdose and misuse: retrospective cohort study
Association of Sex With Recurrence of Autism Spectrum Disorder Among Siblings