5 citations · 12 across the 7 of their papers we have counts for
7 papers
Position: Stop Chasing the C-index when Evaluating Survival Analysis Models
Christian Marius Lillelund, Shi-ang Qi, Russell Greiner +1
The current state of evaluation in survival analysis is plagued by the persistent use of evaluation metrics in ways that are misaligned with the stated modeling objective. In addit…
An Explainable and Conformal AI Model to Detect Temporomandibular Joint Involvement in Children Suffering from Juvenile Idiopathic Arthritis
Lena Todnem Bach Christensen, Dikte Straadt, Stratos Vassis +5
Juvenile idiopathic arthritis (JIA) is the most common rheumatic disease during childhood and adolescence. The temporomandibular joints (TMJ) are among the most frequently affected…
RULSurv: A probabilistic survival-based method for early censoring-aware prediction of remaining useful life in ball bearings
Christian Marius Lillelund, Fernando Pannullo, Morten Opprud Jakobsen +2
Predicting the remaining useful life (RUL) of ball bearings is an active area of research, where novel machine learning techniques are continuously being applied to predict degrada…
Efficient Training of Probabilistic Neural Networks for Survival Analysis
Christian Marius Lillelund, Martin Magris, Christian Fischer Pedersen
Variational Inference (VI) is a commonly used technique for approximate Bayesian inference and uncertainty estimation in deep learning models, yet it comes at a computational cost,…
Reusability report: Prostate cancer stratification with diverse biologically-informed neural architectures
Christian Pedersen, Tiberiu Tesileanu, Tinghui Wu +4
In Elmarakeby et al., "Biologically informed deep neural network for prostate cancer discovery", a feedforward neural network with biologically informed, sparse connections (P-NET)…
Predicting Survival Time of Ball Bearings in the Presence of Censoring
Christian Marius Lillelund, Fernando Pannullo, Morten Opprud Jakobsen +1
Ball bearings find widespread use in various manufacturing and mechanical domains, and methods based on machine learning have been widely adopted in the field to monitor wear and s…
Computationally Efficient Labeling of Cancer Related Forum Posts by Non-Clinical Text Information Retrieval
Jimmi Agerskov, Kristian Nielsen, Christian Marius Lillelund +1
An abundance of information about cancer exists online, but categorizing and extracting useful information from it is difficult. Almost all research within healthcare data processi…