1 citations · 1 across the 4 of their papers we have counts for
4 papers
What Matters is the Prompt: Prompt Sensitivity and Prompt Generation in Foundation Models for Lung Nodule Segmentation
Jorge F. Lazo, Xixi Liu, Andreas Hallqvist +5
Lung nodule segmentation in computed tomography is essential for extracting clinically relevant information for lung cancer assessment and treatment planning. Foundation models hav…
CT-CLIP Representations for Multimodal Lung Cancer Survival Prediction
Sofie Allgöwer, Mikael Johansson, Andreas Hallqvist +4
Accurate prognosis prediction is important for treatment planning in lung cancer, but deep learning-driven survival modelling is often limited by the scarcity of curated imaging co…
Medical Image Understanding Improves Survival Prediction via Visual Instruction Tuning
Xixi Liu, Jorge Lazo, Andreas Hallqvist +8
Accurate prognostication and risk estimation are essential for guiding clinical decision-making and optimizing patient management. While radiologist-assessed features from CT scans…
Inferring origin-destination distribution of agent transfer in a complex network using deep gated recurrent units
Vee-Liem Saw, Luca Vismara, Suryadi +3
Predicting the origin-destination (OD) probability distribution of agent transfer is an important problem for managing complex systems. However, prediction accuracy of associated s…