Abstract: In this research, an Artificial Neural Network (ANN) model was developed and tested to predict efficiency of antibiotics in treating various bacteria types. Attributes that were taken in account are: organism name, specimen type, and antibiotic name as input and susceptibility as an output. A model based on one input, one hidden, and one output layers concept topology was developed and trained using a data from Queensland government's website. The evaluation shows that the ANN model is capable of correctly predicting the susceptibility of organisms to the antibiotics with 98% accuracy
Background The rise of antibiotic resistance in pathogenic bacteria is a significant problem for ...
Background: A correct approach to recurrent urinary tract infections (rUTIs) is an important pillar ...
Background The rise of antibiotic resistance in pathogenic bacteria is a significant problem for ...
Abstract: In this research, an Artificial Neural Network (ANN) model was developed and tested to pre...
Abstract: In this research, an Artificial Neural Network (ANN) model was developed and validated to ...
An adequate model for predicting bacteraemia has not yet been developed. This study aimed to evaluat...
It is well known that Bacillus species produce a wide variety of metabolites with interesting biolog...
Antibiotic resistance (AR) is a naturally occurring phenomenon with the capacity to render useless a...
Antibiotic resistance poses a major threat to public health. More effective ways of the antibiotic p...
BACKGROUND: The rise of antibiotic resistance in pathogenic bacteria is a significant problem for th...
Antimicrobial Resistance (AMR) is a growing concern in the medical field. Over-prescription of antib...
The study of the quantitative structure–activity relationship (QSAR) on antibacterial activity in a ...
This study introduces an innovative approach to antibiotic optimization and improved infectious dise...
Machine learning (ML) algorithms are increasingly applied in medical research and in healthcare, gra...
Artificial Neural Network (ANN) analysis is shown to predict the molecular properties of new anti-EB...
Background The rise of antibiotic resistance in pathogenic bacteria is a significant problem for ...
Background: A correct approach to recurrent urinary tract infections (rUTIs) is an important pillar ...
Background The rise of antibiotic resistance in pathogenic bacteria is a significant problem for ...
Abstract: In this research, an Artificial Neural Network (ANN) model was developed and tested to pre...
Abstract: In this research, an Artificial Neural Network (ANN) model was developed and validated to ...
An adequate model for predicting bacteraemia has not yet been developed. This study aimed to evaluat...
It is well known that Bacillus species produce a wide variety of metabolites with interesting biolog...
Antibiotic resistance (AR) is a naturally occurring phenomenon with the capacity to render useless a...
Antibiotic resistance poses a major threat to public health. More effective ways of the antibiotic p...
BACKGROUND: The rise of antibiotic resistance in pathogenic bacteria is a significant problem for th...
Antimicrobial Resistance (AMR) is a growing concern in the medical field. Over-prescription of antib...
The study of the quantitative structure–activity relationship (QSAR) on antibacterial activity in a ...
This study introduces an innovative approach to antibiotic optimization and improved infectious dise...
Machine learning (ML) algorithms are increasingly applied in medical research and in healthcare, gra...
Artificial Neural Network (ANN) analysis is shown to predict the molecular properties of new anti-EB...
Background The rise of antibiotic resistance in pathogenic bacteria is a significant problem for ...
Background: A correct approach to recurrent urinary tract infections (rUTIs) is an important pillar ...
Background The rise of antibiotic resistance in pathogenic bacteria is a significant problem for ...