9 papers
Surv-IPTB: An Attention-Based Model for Estimating Individual Probability of Treatment Benefit with Survival Data
Lev V. Utkin, Stanislav K. Kogan, Andrei V. Konstantinov
This work presents a novel attention-based framework for estimating the Individual Probability of Treatment Benefit (IPTB) in survival analysis contexts. The proposed model, called…
Attention-Based Estimation of the Individual Treatment Benefit Probability under Dose Variation
Lev V. Utkin, Andrei V. Konstantinov, Stanislav K. Kogan +2
Estimating the probability that a treatment outperforms a control for an individual patient, called the Individual Probability of Treatment Benefit (IPTB), offers a clinically intu…
SDPM: Survival Diffusion Probabilistic Model for Continuous-Time Survival Analysis
Stanislav R. Kirpichenko, Andrei V. Konstantinov, Lev V. Utkin
Survival analysis aims to estimate a time-to-event distribution from data with censored observations. Many existing methods either impose structural assumptions on the hazard funct…
Towards a Relationship-Aware Transformer for Tabular Data
Andrei V. Konstantinov, Valerii A. Zuev, Lev V. Utkin
Deep learning models for tabular data typically do not allow for imposing a graph of external dependencies between samples, which can be useful for accounting for relatedness in ta…
Survival Analysis as Imprecise Classification with Trainable Kernels
Andrei V. Konstantinov, Vlada A. Efremenko, Lev V. Utkin
Survival analysis is a fundamental tool for modeling time-to-event data in healthcare, engineering, and finance, where censored observations pose significant challenges. While trad…
Ensemble-Based Survival Models with the Self-Attended Beran Estimator Predictions
Lev V. Utkin, Semen P. Khomets, Vlada A. Efremenko +2
Survival analysis predicts the time until an event of interest, such as failure or death, but faces challenges due to censored data, where some events remain unobserved. Ensemble-b…