alzheimer's disease 1clinical data 1imputation-free learning 1transformer models 1uncertainty quantification 1
From the 1 of 2 linked papers with an AI index.
2 papers
q-bio.NC2026
Imputation-free transformer learning enables robust Alzheimer's disease prediction and calibrated uncertainty quantification across heterogeneous clinical cohorts
Christelle Schneuwly Diaz, Narmina Baghirova, Duy-Thanh Vu +4
The paper introduces NITROGEN, an imputation‑free transformer that learns from partially observed clinical records to predict Alzheimer's disease diagnosis and cognitive scores whi…
eess.SP2024
SzCORE: A Seizure Community Open-source Research Evaluation framework for the validation of EEG-based automated seizure detection algorithms
Jonathan Dan, Una Pale, Alireza Amirshahi +9
The need for high-quality automated seizure detection algorithms based on electroencephalography (EEG) becomes ever more pressing with the increasing use of ambulatory and long-ter…