Applications of machine learning to the problem of antimicrobial resistance: an emerging model for translational research
Antimicrobial resistance (AMR) remains one of the most challenging phenomena of modern
medicine. Machine learning (ML) is a subfield of artificial intelligence that focuses on the …
medicine. Machine learning (ML) is a subfield of artificial intelligence that focuses on the …
TransAMR: an interpretable transformer model for accurate prediction of antimicrobial resistance using antibiotic administration data
M Tharmakulasingam, W Wang, M Kerby… - IEEE …, 2023 - ieeexplore.ieee.org
Antimicrobial Resistance (AMR) is a growing public and veterinary health concern, and the
ability to accurately predict AMR from antibiotics administration data is crucial for effectively …
ability to accurately predict AMR from antibiotics administration data is crucial for effectively …
Learning to search efficiently for causally near-optimal treatments
S Håkansson, V Lindblom… - Advances in …, 2020 - proceedings.neurips.cc
Finding an effective medical treatment often requires a search by trial and error. Making this
search more efficient by minimizing the number of unnecessary trials could lower both costs …
search more efficient by minimizing the number of unnecessary trials could lower both costs …
[PDF][PDF] A survey of medical image analysis based on machine learning techniques
RJ Al Gharrawi, AA Al-Joda - Journal of Al-Qadisiyah for computer science …, 2023 - iasj.net
Machine learning is a result of the availability and accessibility of a massive amount of data
collected via sensors and the internet. The concept of machine learning demonstrates and …
collected via sensors and the internet. The concept of machine learning demonstrates and …
[PDF][PDF] Interpretable machine learning models to predict antimicrobial resistance
M Tharmakulasingam - 2023 - openresearch.surrey.ac.uk
Antimicrobial resistance (AMR) is a growing global public health concern due to the rapid
emergence and spread of resistant bacteria and other pathogens. Machine learning (ML) …
emergence and spread of resistant bacteria and other pathogens. Machine learning (ML) …
Trans AMR: An Interpretable Transformer Model for Accurate Prediction of Antimicrobial Resistance using Antibiotic Administration Data
T Mukunthan, W Wenwu, K Michael, R Roberto Lo… - 2023 - repo.lib.jfn.ac.lk
AntimicrobialResistance (AMR) isagrowingpublicandveterinaryhealthconcern, andthe abilitytoaccuratelypredictAMRfromantibiotic…
managinginfections. Whilegenomics-basedapproachescanprovidebetterresults …
managinginfections. Whilegenomics-basedapproachescanprovidebetterresults …
Early detection of antimicrobial drug resistance for salmonella typhistrains using machine learning techniques in Rwanda
C Benta - 2021 - dr.ur.ac.rw
Introduction: Antimicrobial drug resistance to Salmonella Typhi is among complex risk
factors for morbidity and mortality, thus of global public health concern. Antimicrobial …
factors for morbidity and mortality, thus of global public health concern. Antimicrobial …
Minimizing search time for finding an effective treatment: Learning a near-optimal policy using constrained algorithms, approximations, and causal inference
S Håkansson, V Lindblom - 2020 - odr.chalmers.se
Patients sometimes have to try several treatments before the one that best alleviates their
symptoms is found. Since each trial of an unsuccessful treatment can be both costly and …
symptoms is found. Since each trial of an unsuccessful treatment can be both costly and …