Raman spectra‐based deep learning: A tool to identify microbial contamination

Author:

Maruthamuthu Murali K.12,Raffiee Amir Hossein3,De Oliveira Denilson Mendes4,Ardekani Arezoo M.3ORCID,Verma Mohit S.125ORCID

Affiliation:

1. Birck Nanotechnology Center Purdue University West Lafayette IN USA

2. Department of Agricultural and Biological Engineering Purdue University West Lafayette IN USA

3. School of Mechanical Engineering Purdue University West Lafayette IN USA

4. Department of Chemistry Purdue University West Lafayette IN USA

5. Weldon School of Biomedical Engineering Purdue University West Lafayette IN USA

Funder

Purdue University

Division of Chemical, Bioengineering, Environmental, and Transport Systems

Publisher

Wiley

Subject

Microbiology

Reference26 articles.

1. Environmental microbial contamination in a stem cell bank;Cobo F.;Letters in Applied Microbiology,2020

2. Water structural transformation at molecular hydrophobic interfaces

3. Cleaning and disinfection of Bacillus cereus biofilm;Deal A.;PDA Journal of Pharmaceutical Science and Technology,2016

4. Deep Residual Learning for Image Recognition(2016). Retrieved fromhttps://www.compu​ter.org/csdl/proce​eding​s-artic​le/cvpr/2016/8851a​770/12OmN​xvwoXv

5. Comprehensive evaluation of compendial USP<71>, BacT/Alert Dual‐T, and Bactec FX for detection of product sterility testing contaminants;England M. R.;Journal of Clinical Microbiology,2019

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