publications

2026

1. The Safety-Aware Denoiser for Text Diffusion Models

   Amman Yusuf, Zhejun Jiang, and Mijung Park

   In International Conference on Machine Learning (ICML), 2026

   Code

2025

1. Training-Free Safe Denoisers for Safe Use of Diffusion Models

   Mingyu Kim, Dongjun Kim, Amman Yusuf, and 2 more authors

   In Advances in Neural Information Processing Systems, 2025

2024

1. Text analysis framework for identifying mutations among non-small cell lung cancer patients from laboratory data

   Amman Yusuf, D. J. Boyne, D. E. O’Sullivan, and 4 more authors

   BMC Medical Research Methodology, Mar 2024

   Abs

   Laboratory data can provide great value to support research aimed at reducing the incidence, prolonging survival and enhancing outcomes of cancer. Data is characterized by the information it carries and the format it holds. Data captured in Alberta’s biomarker laboratory repository is free text, cluttered and rogue. Such data format limits its utility and prohibits broader adoption and research development. Text analysis for information extraction of unstructured data can change this and lead to more complete analyses. Previous work on extracting relevant information from free text, unstructured data employed Natural Language Processing (NLP), Machine Learning (ML), rule-based Information Extraction (IE) methods, or a hybrid combination between them.

2023

1. The impact of population-based EGFR testing in non-squamous metastatic non-small cell lung cancer in Alberta, Canada

   D. R. Brenner, D. E. O’Sullivan, T. N. Jarada, and 7 more authors

   Lung Cancer, 2023

   Abs DOI

   Objectives: While Epidermal Growth Factor Receptor (EGFR) Tyrosine Kinase Inhibitors have been shown to be effective in phase III randomized trials, the value of targeted therapies has been challenging to evaluate at the population-level. We examined the impact of population-level EGFR testing and treatment on survival outcomes among non-squamous metastatic Non-Small Cell Lung Cancer (NSCLC) patients. Materials and methods: Real-world, population-level data were collected from all de novo non-squamous metastatic NSCLC patients in Alberta, Canada from 2004 to 2020. EGFR testing data were collected through Alberta Precision Laboratories. Differences in survival rates and overall survival (OS) pre (2004-2012) and post initiation (post) (2013-2019) testing periods were evaluated using interrupted time series analyses. The impact of testing and subsequent treatment was evaluated using multivariable Cox Proportional Hazards models. Results: In total, 4,578 non-squamous metastatic NSCLC patients were diagnosed pre-EGFR testing and 4,457 patients were diagnosed post-EGFR testing (2013-2019). After adjusting for baseline patient and clinical characteristics, OS in the post-EGFR period was significantly improved compared to the pre-EGFR period (HR: 0.81; 95% CI: 0.78-0.85). Conclusion: These results show the considerable impact of population-based molecular testing and subsequent targeted therapies on survival among metastatic NSCLC patients.

2022

1. Prevalence, Treatment Patterns, and Outcomes of Individuals with EGFR Positive Metastatic Non-Small Cell Lung Cancer in a Canadian Real-World Setting: A Comparison of Exon 19 Deletion, L858R, and Exon 20 Insertion EGFR Mutation Carriers

   D. E. O’Sullivan, T. N. Jarada, Amman Yusuf, and 11 more authors

   Current Oncology, 2022

   Abs DOI

   Real-world evidence surrounding EGFR positive NSCLC patients in Canada is limited. Administrative databases in Alberta, Canada were used to evaluate EGFR testing and mutation prevalence in de novo metastatic NSCLC, as well as the characteristics, treatment patterns, and outcomes of individuals with Exon 19, L858R and Exon20ins mutations. Between 2013-2019, 2974 individuals underwent EGFR testing, of which 451 (15.2%) were EGFR positive. Among EGFR positive individuals, 221 (49.0%) had an Exon 19 mutation, 159 (35.3%) had an L858R mutation, and 18 (4%) had an Exon20ins mutation. The Exon20ins cohort had worse median overall survival from initiation of 1L systemic therapy (10.5 months) than the Exon19 (20.6 months) and L858R cohorts (19.1 months). These findings highlight that Exon20ins mutations represent a rare subset of NSCLC in which treatment options are limited and survival outcomes are worse relative to individuals with more common types of EGFR mutations.