activity
20202025
most citedTemporal Pointwise Convolutional Networks for Length of Stay Prediction in the Intensive Care Unit

59 citations · 71 across the 7 of their papers we have counts for

collaborators

7 papers

cs.LG2025

Reflections from Research Roundtables at the Conference on Health, Inference, and Learning (CHIL) 2025

Emily Alsentzer, Marie-Laure Charpignon, Bill Chen +90

The 6th Annual Conference on Health, Inference, and Learning (CHIL 2025), hosted by the Association for Health Learning and Inference (AHLI), was held in person on June 25-27, 2025…

cs.LG2025

Bridging Graph and State-Space Modeling for Intensive Care Unit Length of Stay Prediction

Shuqi Zi, Haitz Sáez de Ocáriz Borde, Emma Rocheteau +1

Predicting a patient's length of stay (LOS) in the intensive care unit (ICU) is a critical task for hospital resource management, yet remains challenging due to the heterogeneous a…

cs.LG2021

A collection of the accepted abstracts for the Machine Learning for Health (ML4H) symposium 2021

Fabian Falck, Yuyin Zhou, Emma Rocheteau +7

A collection of the accepted abstracts for the Machine Learning for Health (ML4H) symposium 2021. This index is not complete, as some accepted abstracts chose to opt-out of inclusi…

cs.LG2021★ 5 cited

Predicting Patient Outcomes with Graph Representation Learning

Emma Rocheteau, Catherine Tong, Petar Veličković +2

Recent work on predicting patient outcomes in the Intensive Care Unit (ICU) has focused heavily on the physiological time series data, largely ignoring sparse data such as diagnose…

cs.CV2020★ 4 cited

Deep Transfer Learning for Automated Diagnosis of Skin Lesions from Photographs

Emma Rocheteau, Doyoon Kim

Melanoma is not the most common form of skin cancer, but it is the most deadly. Currently, the disease is diagnosed by expert dermatologists, which is costly and requires timely ac…

cs.LG2020★ 59 cited

Temporal Pointwise Convolutional Networks for Length of Stay Prediction in the Intensive Care Unit

Emma Rocheteau, Pietro Liò, Stephanie Hyland

The pressure of ever-increasing patient demand and budget restrictions make hospital bed management a daily challenge for clinical staff. Most critical is the efficient allocation…

cs.LG2020★ 3 cited

Predicting Length of Stay in the Intensive Care Unit with Temporal Pointwise Convolutional Networks

Emma Rocheteau, Pietro Liò, Stephanie Hyland

The pressure of ever-increasing patient demand and budget restrictions make hospital bed management a daily challenge for clinical staff. Most critical is the efficient allocation…