Data

Machine learning and detection of Trichuris muris in mice

The University of Queensland
Dr Maggy Lord (Aggregated by) Dr Maggy Lord (Aggregated by) Dr Silvia Ciocchetta (Aggregated by) Dr Silvia Ciocchetta (Aggregated by) Mrs Tharanga Kariyawasam (Aggregated by)
Viewed: [[ro.stat.viewed]] Cited: [[ro.stat.cited]] Accessed: [[ro.stat.accessed]]
ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rfr_id=info%3Asid%2FANDS&rft_id=info:doi10.48610/7f11f9f&rft.title=Machine learning and detection of Trichuris muris in mice&rft.identifier=RDM ID: bb1703a0-5b6b-11ee-9304-15151f9b6acc&rft.publisher=The University of Queensland&rft.description=Raw near-infrared spectra collected from faecal, blood, serum samples and non-invasively through the skin, of Trichuris infected and uninfected mice. Ten mice were orally infected with T. muris eggs for the low dose group, 10 mice for the high dose group, and 10 mice were used as the control group. Using the NIRS technique, faecal, serum, whole blood samples and mice non-invasively through their skin were scanned over a period of 6 weeks post infection. The collected spectra coupled with machine learning were used to detect Trichuris muris.&rft.creator=Dr Maggy Lord&rft.creator=Dr Maggy Lord&rft.creator=Dr Silvia Ciocchetta&rft.creator=Dr Silvia Ciocchetta&rft.creator=Mrs Tharanga Kariyawasam&rft.creator=Mrs Tharanga Kariyawasam&rft.date=2023&rft_rights= http://guides.library.uq.edu.au/deposit_your_data/terms_and_conditions&rft_subject=eng&rft_subject=Medical Parasitology&rft_subject=MEDICAL AND HEALTH SCIENCES&rft_subject=MEDICAL MICROBIOLOGY&rft.type=dataset&rft.language=English Access the data
Cite Saved to MyRDA Save to MyRDA

Licence & Rights:

Other view details

Access:

Restrictions apply

Contact Information

[email protected]
School of Public Health

Full description

Raw near-infrared spectra collected from faecal, blood, serum samples and non-invasively through the skin, of Trichuris infected and uninfected mice. Ten mice were orally infected with T. muris eggs for the low dose group, 10 mice for the high dose group, and 10 mice were used as the control group. Using the NIRS technique, faecal, serum, whole blood samples and mice non-invasively through their skin were scanned over a period of 6 weeks post infection. The collected spectra coupled with machine learning were used to detect Trichuris muris.

Issued: 26 09 2023

This dataset is part of a larger collection

Click to explore relationships graph
Help

Related Data

Related People

Related Grants and Projects

Related Websites

Subjects
Medical and Health Sciences | Medical Microbiology | Medical Parasitology | eng |

User Contributed Tags    

Login to tag this record with meaningful keywords to make it easier to discover

Other Information
Identifiers
ACN 633 798 857