Pivotal role of artificial intelligence in enhancing experimental animal model research: A machine learning perspective (Record no. 21878)
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| 003 - CONTROL NUMBER IDENTIFIER | |
| control field | OSt |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20241210102748.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 241210b xxu||||| |||| 00| 0 eng d |
| 040 ## - CATALOGING SOURCE | |
| Original cataloging agency | AIKTC-KRRC |
| Transcribing agency | AIKTC-KRRC |
| 100 ## - MAIN ENTRY--PERSONAL NAME | |
| 9 (RLIN) | 24730 |
| Author | Ghosh, Anushka |
| 245 ## - TITLE STATEMENT | |
| Title | Pivotal role of artificial intelligence in enhancing experimental animal model research: A machine learning perspective |
| 250 ## - EDITION STATEMENT | |
| Volume, Issue number | Vol.56(1), Jan-Feb |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. | |
| Place of publication, distribution, etc. | Mumbai |
| Name of publisher, distributor, etc. | Wolter Kluwer |
| Year | 2024 |
| 300 ## - PHYSICAL DESCRIPTION | |
| Pagination | 1-3p. |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc. | Artificial intelligence (AI) refers to a computer imitating “intellectual processes characteristic of humans, such as the ability to reason, discover meaning, generalize, or learn from past experience.”[1] Machine learning (ML) is a core area of AI to create predictive models by learning from data and gradually enhancing the capacity for prediction through experience.[2] The integration of AI and ML into animal research has shown promising potential to enhance translation and reproducibility, complementing traditional approaches such as animal models. AI and ML can optimize preclinical studies using animal models by analyzing complex datasets, improving experimental design, and predicting outcomes. This integration enables researchers to extract more meaningful information from animal experiments.[3] Combining AI/ML analyses of animal model data with human clinical data allows for better translation of findings. This integrated approach helps bridge the gap between preclinical and clinical studies, increasing the relevance of animal model findings to human disease. A combination of transcriptomic analysis (studying gene expression patterns) in postmortem human brain tissue from Alzheimer’s disease patients and mouse models of Alzheimer’s disease was done with the help of ML to identify dysregulated pathways associated with excitatory neurotransmission, a process crucial for brain function.[4] |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| 9 (RLIN) | 4774 |
| Topical term or geographic name entry element | PHARMACOLOGY |
| 700 ## - ADDED ENTRY--PERSONAL NAME | |
| 9 (RLIN) | 19130 |
| Co-Author | Choudhary, Gajendra |
| 773 0# - HOST ITEM ENTRY | |
| Place, publisher, and date of publication | Andheri - Mumbai Wolters Kluwer India Private Limited |
| Title | Indian Journal of Pharmacology |
| International Standard Serial Number | 0253-7613 |
| 856 ## - ELECTRONIC LOCATION AND ACCESS | |
| URL | https://journals.lww.com/iphr/fulltext/2024/01000/the_pivotal_role_of_artificial_intelligence_in.1.aspx |
| Link text | Click here |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Source of classification or shelving scheme | Dewey Decimal Classification |
| Koha item type | Articles Abstract Database |
| Withdrawn status | Lost status | Source of classification or shelving scheme | Damaged status | Not for loan | Home library | Current library | Shelving location | Date acquired | Total Checkouts | Barcode | Date last seen | Price effective from | Koha item type |
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| Dewey Decimal Classification | School of Pharmacy | School of Pharmacy | Archieval Section | 10/12/2024 | 2024-1515 | 10/12/2024 | 10/12/2024 | Articles Abstract Database |