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Antimicrobial resistance (AMR) is a growing public health threat, estimated to cause over 10 million deaths per year and cost the global economy 100 trillion USD by 2050 under status quo projections. These losses would mainly result from an…

Biological datasets amenable to applied machine learning are more available today than ever before, yet they lack adequate representation in the Data-for-Good community. Here we present a work in progress case study performing analysis on…

Machine Learning · Statistics 2016-07-06 John W. Santerre , James J. Davis , Fangfang Xia , Rick Stevens

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…

Antimicrobial resistance (AMR) is a risk for patients and a burden for the healthcare system. However, AMR assays typically take several days. This study develops predictive models for AMR based on easily available clinical and…

Antimicrobial resistance (AMR) poses a significant threat to public health by increasing mortality, extending hospital stays, and increasing healthcare costs. It affects people of all ages and affects health services, veterinary medicine,…

Dynamical Systems · Mathematics 2023-06-12 Alissen Peterson , Jhoana P. Romero-Leiton , Pablo Aguirre , Kamal R. Acharya , Bouchra Nasri

Antimicrobial resistance (AMR) poses a mounting global health crisis, requiring rapid and reliable prediction frameworks that capture its complex evolutionary dynamics. Traditional antimicrobial susceptibility testing (AST), while accurate,…

Populations and Evolution · Quantitative Biology 2025-11-18 Anshul Bagaria

Background: Antimicrobial resistance (AMR) is a major global public health problem, contributing to an estimated 4.95 million deaths in 2019 and projected to cause up to 10 million deaths annually and 100 trillion dollars in cumulative…

Populations and Evolution · Quantitative Biology 2026-01-06 Felipe Schardong , Claudio Jose Struchiner , Luiz Max Carvalho

Antibiotic resistance is a growing public health problem. To gain a fundamental understanding of resistance evolution, a combination of systematic experimental and theoretical approaches is required. Evolution experiments combined with…

Populations and Evolution · Quantitative Biology 2021-05-24 Gabriela Petrungaro , Yuval Mulla , Tobias Bollenbach

Traditional drug discovery is a long, expensive, and complex process. Advances in Artificial Intelligence (AI) and Machine Learning (ML) are beginning to change this narrative. Here, we provide a comprehensive overview of different AI and…

Artificial Intelligence · Computer Science 2024-11-12 Khartik Uppalapati , Eeshan Dandamudi , S. Nick Ice , Gaurav Chandra , Kirsten Bischof , Christian L. Lorson , Kamal Singh

Antimicrobial resistance (AMR) poses a global health threat, reducing the effectiveness of antibiotics and complicating clinical decision-making. To address this challenge, we introduce abx_amr_simulator, a Python-based simulation package…

Machine Learning · Computer Science 2026-03-13 Joyce Lee , Seth Blumberg

The worldwide increase of antimicrobial resistance (AMR) is a serious threat to human health. To avert the spread of AMR, fast reliable diagnostics tools that facilitate optimal antibiotic stewardship are an unmet need. In this regard,…

Antimicrobial resistance is an important public health concern that has implications in the practice of medicine worldwide. Accurately predicting resistance phenotypes from genome sequences shows great promise in promoting better use of…

In this research, medical information from 1200 patients across various hospitals in Iraq was collected over a period of 3 years, from February 3, 2018, to March 5, 2021. The study encompassed several infections, including urinary tract…

Other Quantitative Biology · Quantitative Biology 2023-07-28 Maitham G. Yousif

Can we understand and predict the evolutionary pathways by which bacteria acquire multi-drug resistance (MDR)? These questions have substantial potential impact in basic biology and in applied approaches to address the global health…

Populations and Evolution · Quantitative Biology 2024-11-05 Jessica Renz , Kazeem A. Dauda , Olav N. L. Aga , Ramon Diaz-Uriarte , Iren H. Löhr , Bjørn Blomberg , Iain G. Johnston

Electronic health records (EHR) is an inherently multimodal register of the patient's health status characterized by static data and multivariate time series (MTS). While MTS are a valuable tool for clinical prediction, their fusion with…

Antibiotics are the wonder discoveries to combat microbes. For decades, multiple varieties of antibiotics have been used for therapeutic purposes in hospital settings and communities throughout the world. Unfortunately, bacteria have become…

Other Quantitative Biology · Quantitative Biology 2019-08-13 Fazlul MKK , Shah Samiur Rashid , Nazmul MHM , Zaidul I. S. M , Roesnita Baharudin , Aizi Nor Mazila Ramli

Skin and soft tissue infections (SSTIs) are among the most frequently observed diseases in ambulatory and hospital settings. Resistance of diverse bacterial pathogens to antibiotics is a significant cause of severe SSTIs, and treatment…

Machine Learning · Computer Science 2022-03-01 Farnaz H. Foomani , Shahzad Mirza , Sahjid Mukhida , Kannuri Sriram , Zeyun Yu , Aayush Gupta , Sandeep Gopalakrishnan

Antibiotic resistance constitutes a major health threat. Predicting bacterial causes of infections is key to reducing antibiotic misuse, a leading driver of antibiotic resistance. We train a machine learning algorithm on administrative and…

General Economics · Economics 2019-06-10 Michael Allan Ribers , Hannes Ullrich

The rapid emergence of antibiotic-resistant bacteria is recognized as a global healthcare crisis, undermining the efficacy of life-saving antibiotics. This crisis is driven by the improper and overuse of antibiotics, which escalates…

Machine Learning · Computer Science 2024-06-03 Simon A. Lee , Trevor Brokowski , Jeffrey N. Chiang

Purpose: Antimicrobial resistance is a major global health concern, affecting hospital admissions and treatment success. This study aims to introduce an experimental setup for monitoring bacterial activity over time using image-based…

Quantitative Methods · Quantitative Biology 2025-06-12 M. A. Gameiro , R. F. Pinto , N. V. Lopes
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