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Related papers: Predicting Antimicrobial Resistance in the Intensi…

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New antibiotics are needed to battle growing antibiotic resistance, but the development process from hit, to lead, and ultimately to a useful drug, takes decades. Although progress in molecular property prediction using machine-learning…

Early identification of patients at risk for clinical deterioration in the intensive care unit (ICU) remains a critical challenge. Delayed recognition of impending adverse events, including mortality, vasopressor initiation, and mechanical…

Machine Learning · Computer Science 2026-03-17 Binesh Sadanandan

Mastitis is a billion dollar health problem for the modern dairy industry, with implications for antibiotic resistance. The use of AI techniques to identify the early onset of this disease, thus has significant implications for the…

Machine Learning · Computer Science 2021-01-08 Cathal Ryan , Christophe Guéret , Donagh Berry , Medb Corcoran , Mark T. Keane , Brian Mac Namee

One's present repertoire of antibodies encodes the history of one's past immunological experience. Can the present autoantibody repertoire be consulted to predict resistance or susceptibility to the future development of an autoimmune…

Tissues and Organs · Quantitative Biology 2009-11-10 Francisco J. Quintana , Peter H. Hagedorn , Gad Elizur , Yifat Marbel , Eytan Domany , Irun R. Cohen

Antimicrobial resistance is an emerging global health crisis that is undermining advances in modern medicine and, if unmitigated, threatens to kill 10 million people per year worldwide by 2050. Research over the last decade has demonstrated…

Quantitative Methods · Quantitative Biology 2020-09-24 K. Farquhar , H. Flohr , D. A. Charlebois

Rapid identification of bacteria is essential to prevent the spread of infectious disease, help combat antimicrobial resistance, and improve patient outcomes. Raman optical spectroscopy promises to combine bacterial detection,…

Predicting extubation failure in intensive care is challenging due to complex data and the severe consequences of inaccurate predictions. Machine learning shows promise in improving clinical decision-making but often fails to account for…

Machine Learning · Computer Science 2024-12-03 Akram Yoosoofsah

Insulin resistance (IR) is a key precursor to diabetes and a significant risk factor for cardiovascular disease. Traditional IR assessment methods require multiple blood tests. We developed a simple AI model using only fasting blood glucose…

Machine Learning · Computer Science 2025-03-10 Weihao Gao , Zhuo Deng , Zheng Gong , Ziyi Jiang , Lan Ma

Urinary Tract Infection (UTIs) is referred as one of the most common infection in medical sectors worldwide and antimicrobial resistance (AMR) is also a global threat to human that is related with many diseases. As antibiotics used for the…

Machine learning is increasingly used to discover diagnostic and prognostic biomarkers from high-dimensional molecular data. However, a variety of factors related to experimental design may affect the ability to learn generalizable and…

Respiratory failure is the one of major causes of death in critical care unit. During the outbreak of COVID-19, critical care units experienced an extreme shortage of mechanical ventilation because of respiratory failure related syndromes.…

Machine Learning · Computer Science 2021-09-08 Yilin Yin , Chun-An Chou

We present a machine learning pipeline and model that uses the entire uncurated EHR for prediction of in-hospital mortality at arbitrary time intervals, using all available chart, lab and output events, without the need for pre-processing…

Machine Learning · Computer Science 2019-09-18 Jacob Deasy , Pietro Liò , Ari Ercole

ICU readmission is associated with longer hospitalization, mortality and adverse outcomes. An early recognition of ICU re-admission can help prevent patients from worse situation and lower treatment cost. As the abundance of Electronics…

Machine Learning · Computer Science 2019-10-08 Zhiheng Li , Xinyue Xing , Bingzhang Lu , Zhixiang Li

Liver infection is a common disease, which poses a great threat to human health, but there is still able to identify an optimal technique that can be used on large-level screening. This paper deals with ML algorithms using different data…

Machine Learning · Computer Science 2023-05-16 P. Deivendran , S. Selvakanmani , S. Jegadeesan , V. Vinoth Kumar

The intestinal microbiota plays important roles in digestion and resistance against entero-pathogens. As with other ecosystems, its species composition is resilient against small disturbances but strong perturbations such as antibiotics can…

Quantitative Methods · Quantitative Biology 2015-06-04 Vanni Bucci , Serena Bradde , Giulio Biroli , Joao B. Xavier

The antibiotics time machine is an optimization question posed by Mira \latin{et al.} on the design of antibiotic treatment plans to minimize antibiotic resistance. The problem is a variation of the Markov decision process. These authors…

Optimization and Control · Mathematics 2015-05-12 Ngoc Mai Tran , Jed Yang

The objective of this work is to develop an Electronic Medical Record (EMR) data processing tool that confers clinical context to Machine Learning (ML) algorithms for error handling, bias mitigation and interpretability. We present…

Postoperative stroke remains a critical complication in elderly surgical intensive care unit (SICU) patients, contributing to prolonged hospitalization, elevated healthcare costs, and increased mortality. Accurate early risk stratification…

Quantitative Methods · Quantitative Biology 2025-06-05 Tinghuan Li , Shuheng Chen , Junyi Fan , Elham Pishgar , Kamiar Alaei , Greg Placencia , Maryam Pishgar

Bacterial resistance to antibiotic treatment is a huge concern: introduction of any new antibiotic is shortly followed by the emergence of resistant bacterial isolates in the clinic. This issue is compounded by a severe lack of new…

Cell Behavior · Quantitative Biology 2014-09-16 Lucy Ternent , Rosemary J. Dyson , Anne-Marie Krachler , Sara Jabbari

The discovery of novel antibiotics is critical to address the growing antimicrobial resistance (AMR). However, pharmaceutical industries face high costs (over $1 billion), long timelines, and a high failure rate, worsened by the rediscovery…

Computation and Language · Computer Science 2025-03-28 Maxime Delmas , Magdalena Wysocka , Danilo Gusicuma , André Freitas
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