Publications related to Multimodal Prediction Framework for Total Shoulder Arthroplasty Outcomes: Integrating Morphological, Musculoskeletal, Finite Element, and Bayesian Causal Models

Related publications (11)

A positivity robust strategy to study effects of switching treatment

In studies of medical treatments, individuals often experience post-treatment events that predict their future outcomes. In this work, we study how to use initial observations of a recurrent event - a type of post-treatment event - to offer updated treatme ...

2025

An Information-Theoretic Framework for Multiplex Graphs

Anda Skeja

This thesis presents a comprehensive theory of information-theoretic measures for characterizing the complexity and higher-order dependence structures of graphs. We introduce multivariate complexity and dependence measures for graphs within the framework o ...

EPFL2024

s-ID: Causal Effect Identification in a Sub-Population

Amir Mohammad Aboueimehrizi, Negar Kiyavash, Ehsan Mokhtarian

Causal inference in a sub-population involves identifying the causal effect of an intervention on a specific subgroup, which is distinguished from the whole population through the influence of systematic biases in the sampling process. However, ignoring th ...

Association for the Advancement of Artificial Intelligence2024

Surgical approaches to the capitellum: a comparative anatomic study

Alexandre Terrier, Patrick Goetti, Frédéric Vauclair

Background: Osteochondritis dissecans (OCD) of the humeral capitellum is an important cause of elbow disability in young athletes. Large and unstable lesions sometimes require joint reconstruction with osteochondral autograft. Several approaches have been ...

Mosby-Elsevier2024

Exploring Defeasibility in Causal Reasoning

Boi Faltings, Antoine Bosselut, Debjit Paul, Shaobo Cui, Mahammad Ismayilzada, Lazar Milikic

Defeasibility in causal reasoning implies that the causal relationship between cause and effect can be strengthened or weakened. Namely, the causal strength between cause and effect should increase or decrease with the incorporation of strengthening argume ...

2024

The stability of deep learning for 21cm foreground removal across various sky models and frequency-dependent systematics

Te Chen, Jean-Paul Richard Kneib, Daniel Felipe Forero Sanchez, Emma Elizabeth Tolley, Michele Bianco

Deep learning (DL) has recently been proposed as a novel approach for 21cm foreground removal. Before applying DL to real observations, it is essential to assess its consistency with established methods, its performance across various simulation models, an ...

2024

Estimation and control under uncertainty with application to power systems

Jean-Sébastien Hubert Brouillon

The transition to sustainable energy demands a fundamental redesign of the electrical grid, especially at the distribution level. With the increasing deployment of distributed energy resources, the development of reliable models, accurate state estimation ...

EPFL2024

Enhancing Prostate Cancer Diagnosis with In-Memory Sensing and Edge Computing of Percent-free PSA Index

Alireza Mafi, Sandro Carrara, Ata Jedari Golparvar, Gian Luca Barbruni

In this paper, we are presenting a new architecture to directly compute the ‘Percent-free PSA’ diagnostics index to enhance the differentiation of prostate cancer from benign prostatic disease. The proposed circuit uses silicon nanowires-based memristive b ...

Institute of Electrical and Electronics Engineers Inc.2024

CRAB: Assessing the Strength of Causal Relationships Between Real-World Events

Karl Aberer, Antoine Bosselut, Syrielle Mathilde Marie Montariol, Debjit Paul, Angeliki Romanou, Léo Jules Laugier

Understanding narratives requires reasoning about the cause-and-effect relationships between events mentioned in the text. While existing foundation models yield impressive results in many NLP tasks requiring reasoning, it is unclear whether they understan ...

Association for Computational Linguistics2023

Better Trees for Santa Claus

Etienne Michel François Bamas, Lars Rohwedder

We revisit the problem max-min degree arborescence, which was introduced by Bateni et al. [STOC'09] as a central special case of the general Santa Claus problem, which constitutes a notorious open question in approximation algorithms. In the former problem ...

Assoc Computing Machinery2023

Soft bioelectronic technologies for selective and multimodal peripheral nerve interfaces

Valentina Marie Paggi

The peripheral nervous system (PNS) regulates the exchange of sensory information and motor commands between the body and the central nervous system. Further, through the autonomic nervous system, the PNS plays a pivotal role in controlling vital physiolog ...

EPFL2023