301 citations
- Imperial College LondonGB5 papers
- University of CambridgeGB4 papers
- University of OxfordGB3 papers
- Addenbrooke's HospitalGB2 papers
- King's College LondonGB2 papers
- National Institutes of HealthUS2 papers
- Queen Mary University of LondonGB2 papers
- Severance HospitalKR2 papers
- Universidad Autónoma de MadridES2 papers
- University of PisaIT2 papers
- Barts Health NHS TrustGB1 paper
- California Institute of TechnologyUS1 paper
16 papers
Automating Pharmacovigilance Evidence Generation: Using Large Language Models to Produce Context-Aware SQL
Jeffery L. Painter, Venkateswara Rao Chalamalasetti, Raymond Kassekert +1
Objective: To enhance the efficiency and accuracy of information retrieval from pharmacovigilance (PV) databases by employing Large Language Models (LLMs) to convert natural langua…
Improved Galactic Foreground Removal for B-Modes Detection with Clustering Methods
Giuseppe Puglisi, Gueorgui Mihaylov, Georgia V. Panopoulou +4
Characterizing the sub-mm Galactic emission has become increasingly critical especially in identifying and removing its polarized contribution from the one emitted by the Cosmic Mi…
Image-level Harmonization of Multi-Site Data using Image-and-Spatial Transformer Networks
R. Robinson, Q. Dou, D. C. Castro +5
We investigate the use of image-and-spatial transformer networks (ISTNs) to tackle domain shift in multi-site medical imaging data. Commonly, domain adaptation (DA) is performed wi…
Meta-Learning GNN Initializations for Low-Resource Molecular Property Prediction
Cuong Q. Nguyen, Constantine Kreatsoulas, Kim M. Branson
Building in silico models to predict chemical properties and activities is a crucial step in drug discovery. However, limited labeled data often hinders the application of deep lea…
Considering discrepancy when calibrating a mechanistic electrophysiology model
Chon Lok Lei, Sanmitra Ghosh, Dominic G. Whittaker +14
Uncertainty quantification (UQ) is a vital step in using mathematical models and simulations to take decisions. The field of cardiac simulation has begun to explore and adopt UQ me…
Randomized Block Proximal Methods for Distributed Stochastic Big-Data Optimization
Francesco Farina, Giuseppe Notarstefano
In this paper we introduce a class of novel distributed algorithms for solving stochastic big-data convex optimization problems over directed graphs. In the addressed set-up, the d…