10 papers · 1 filter
RocketPFN: Accurate Time Series Classification via In-Context Learning
Franco Martino O'Rourke, Ana Trisovic, Dimitris Bertsimas
We introduce RocketPFN, a training-free pipeline for time series classification that combines random convolutional feature extraction (Rocket) with in-context classification via a…
A Causal DAG Prior for Synthetic Time-Series Classification Datasets
Franco Martino O'Rourke, Ana Trisovic, Dimitris Bertsimas
A Prior-data fitted Network learns the posterior predictive induced by its training prior; bringing this paradigm to multivariate time-series classification therefore calls for a s…
Optimal Control of Fluid Restless Multi-armed Bandits: A Machine Learning Approach
Dimitris Bertsimas, Cheol Woo Kim, José Niño-Mora
We present a novel machine learning framework for the optimal control of fluid restless multi-armed bandit problems (FRMABPs) with state equations that are either affine or quadrat…
A Multimodal and Explainable Machine Learning Approach to Diagnosing Multi-Class Ejection Fraction from Electrocardiograms
Catherine Ning, Yu Ma, Cindy Beini Wang +4
Left ventricular ejection fraction (LVEF) assessment depends on echocardiography, limiting access in primary care and resource-constrained settings. We developed a multimodal machi…
Early Warning Index for Patient Deteriorations in Hospitals
Dimitris Bertsimas, Yu Ma, Kimberly Villalobos Carballo +5
Hospitals lack automated systems to harness the growing volume of heterogeneous clinical and operational data to effectively forecast critical events. Early identification of patie…
Towards Optimal Valve Prescription for Transcatheter Aortic Valve Replacement (TAVR) Surgery: A Machine Learning Approach
Phevos Paschalidis, Vasiliki Stoumpou, Lisa Everest +11
Transcatheter Aortic Valve Replacement (TAVR) has emerged as a minimally invasive treatment option for patients with severe aortic stenosis, a life-threatening cardiovascular condi…