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Advances in Food and Nutrition Research
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March 1, 2025
Advanced data analytics and "omics" techniques to control enteric foodborne pathogens
Shraddha Karanth, Abani K Pradhan
Risk Analysis : an Official Publication of the Society for Risk Analysis
|
April 12, 2022
Development of a novel machine learning-based weighted modeling approach to incorporate Salmonella enterica heterogeneity on a genetic scale in a dose-response modeling framework
Shraddha Karanth, Abani K Pradhan
Food Research International (Ottawa, Ont.)
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December 21, 2023
A machine learning approach to identifying Salmonella stress response genes in isolates from poultry processing
Edmund O Benefo, Shraddha Karanth, Abani K Pradhan
Frontiers in Microbiology
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July 10, 2023
Linking microbial contamination to food spoilage and food waste: the role of smart packaging, spoilage risk assessments, and date labeling
Shraddha Karanth, Shuyi Feng, Debasmita Patra, et al.
Current Research in Food Science
|
June 28, 2023
Machine learning to predict foodborne salmonellosis outbreaks based on genome characteristics and meteorological trends
Shraddha Karanth, Jitendra Patel, Adel Shirmohammadi, et al.
Food Research International (Ottawa, Ont.)
|
January 4, 2022
Exploring the predictive capability of advanced machine learning in identifying severe disease phenotype in Salmonella enterica
Shraddha Karanth, Collins K Tanui, Jianghong Meng, et al.
Pathogens (Basel, Switzerland)
|
June 24, 2022
A Machine Learning Model for Food Source Attribution of <i>Listeria monocytogenes</i>
Collins K Tanui, Edmund O Benefo, Shraddha Karanth, et al.
Food Research International (Ottawa, Ont.)
|
June 1, 2024
Machine learning to predict the relationship between Vibrio spp. concentrations in seawater and oysters and prevalent environmental conditions
Shuyi Feng, Shraddha Karanth, Esam Almuhaideb, et al.
Bioinformation
|
June 21, 2012
Structure based virtual screening of novel inhibitors against multidrug resistant superbugs
Sinosh Skariyachan, Arpitha Badarinath Mahajanakatti, Narasimha Sharma, et al.
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of 1
Search research articles
Search
Showing results (1-10 of 9) with videos related to
Sort By:
Page
of 1
Advances in Food and Nutrition Research
|
March 1, 2025
Advanced data analytics and "omics" techniques to control enteric foodborne pathogens
Shraddha Karanth, Abani K Pradhan
Risk Analysis : an Official Publication of the Society for Risk Analysis
|
April 12, 2022
Development of a novel machine learning-based weighted modeling approach to incorporate Salmonella enterica heterogeneity on a genetic scale in a dose-response modeling framework
Shraddha Karanth, Abani K Pradhan
Food Research International (Ottawa, Ont.)
|
December 21, 2023
A machine learning approach to identifying Salmonella stress response genes in isolates from poultry processing
Edmund O Benefo, Shraddha Karanth, Abani K Pradhan
Frontiers in Microbiology
|
July 10, 2023
Linking microbial contamination to food spoilage and food waste: the role of smart packaging, spoilage risk assessments, and date labeling
Shraddha Karanth, Shuyi Feng, Debasmita Patra, et al.
Current Research in Food Science
|
June 28, 2023
Machine learning to predict foodborne salmonellosis outbreaks based on genome characteristics and meteorological trends
Shraddha Karanth, Jitendra Patel, Adel Shirmohammadi, et al.
Food Research International (Ottawa, Ont.)
|
January 4, 2022
Exploring the predictive capability of advanced machine learning in identifying severe disease phenotype in Salmonella enterica
Shraddha Karanth, Collins K Tanui, Jianghong Meng, et al.
Pathogens (Basel, Switzerland)
|
June 24, 2022
A Machine Learning Model for Food Source Attribution of <i>Listeria monocytogenes</i>
Collins K Tanui, Edmund O Benefo, Shraddha Karanth, et al.
Food Research International (Ottawa, Ont.)
|
June 1, 2024
Machine learning to predict the relationship between Vibrio spp. concentrations in seawater and oysters and prevalent environmental conditions
Shuyi Feng, Shraddha Karanth, Esam Almuhaideb, et al.
Bioinformation
|
June 21, 2012
Structure based virtual screening of novel inhibitors against multidrug resistant superbugs
Sinosh Skariyachan, Arpitha Badarinath Mahajanakatti, Narasimha Sharma, et al.
Page
of 1