2025/03/08 by Fateme Nateghi Haredasht, Fatemeh Amrollahi, Haredasht, Fateme Nateghi +28
Biochemistry, Genetics and Molecular Biology · Immunology and Microbiology · #Antibiotic Use and Resistance #Applications (stat.AP) #Bacterial Identification and Susceptibility Testing #FOS: Biological sciences #FOS: Computer and information sciences #Information Retrieval (cs.IR) #Machine Learning (cs.LG) #Metabolomics and Mass Spectrometry Studies #Quantitative Methods (q-bio.QM)
paper · pdf · doi:10.48550/arxiv.2503.07664
openalex publication_date 2025/03/08 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
The Antibiotic Resistance Microbiology Dataset (ARMD) is a de-identified resource derived from electronic health records (EHR) that facilitates research in antimicrobial resistance (AMR). ARMD encompasses big data from adult patients collected from over 15 years at two academic-affiliated hospitals, focusing on microbiological cultures, antibiotic susceptibilities, and associated clinical and demographic features. Key attributes include organism identification, susceptibility patterns for 55 antibiotics, implied susceptibility rules, and de-identified patient information. This dataset supports studies on antimicrobial stewardship, causal inference, and clinical decision-making. ARMD is designed to be reusable and interoperable, promoting collaboration and innovation in combating AMR. This paper describes the dataset's acquisition, structure, and utility while detailing its de-identification process.