Revolutionising pharmacy through machine learning: the progress and perils / Yuslina Zakaria
Machine learning (ML) is transforming pharmacy, enhancing accuracy in drug discovery, personalised medicine, and patient care. ML, a branch of artificial intelligence (AI), uses algorithms such as neural networks, decision trees, and support vector machines to learn from large datasets and make pred...
Saved in:
Main Author: | |
---|---|
Format: | Article |
Language: | English |
Published: |
Faculty of Pharmacy
2024
|
Subjects: | |
Online Access: | https://ir.uitm.edu.my/id/eprint/102828/1/102828.pdf https://ir.uitm.edu.my/id/eprint/102828/ |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
id |
my.uitm.ir.102828 |
---|---|
record_format |
eprints |
spelling |
my.uitm.ir.1028282024-09-26T06:56:17Z https://ir.uitm.edu.my/id/eprint/102828/ Revolutionising pharmacy through machine learning: the progress and perils / Yuslina Zakaria Zakaria, Yuslina Drugs and their actions Pharmaceutical technology Machine learning (ML) is transforming pharmacy, enhancing accuracy in drug discovery, personalised medicine, and patient care. ML, a branch of artificial intelligence (AI), uses algorithms such as neural networks, decision trees, and support vector machines to learn from large datasets and make predictions. In pharmaceutical research, ML accelerates the identification of potential drug candidates, improves design optimisation, and increases research efficiency. Additionally, ML in predictive analytics for pharmacy practice shows promising results, highlighting the need for further research and adoption to improve patient care (1). Faculty of Pharmacy 2024-07 Article PeerReviewed text en https://ir.uitm.edu.my/id/eprint/102828/1/102828.pdf Revolutionising pharmacy through machine learning: the progress and perils / Yuslina Zakaria. (2024) Prescription <https://ir.uitm.edu.my/view/publication/Prescription/> (7). |
institution |
Universiti Teknologi Mara |
building |
Tun Abdul Razak Library |
collection |
Institutional Repository |
continent |
Asia |
country |
Malaysia |
content_provider |
Universiti Teknologi Mara |
content_source |
UiTM Institutional Repository |
url_provider |
http://ir.uitm.edu.my/ |
language |
English |
topic |
Drugs and their actions Pharmaceutical technology |
spellingShingle |
Drugs and their actions Pharmaceutical technology Zakaria, Yuslina Revolutionising pharmacy through machine learning: the progress and perils / Yuslina Zakaria |
description |
Machine learning (ML) is transforming pharmacy, enhancing accuracy in drug discovery, personalised medicine, and patient care. ML, a branch of artificial intelligence (AI), uses algorithms such as neural networks, decision trees, and support vector machines to learn from large datasets and make predictions. In pharmaceutical research, ML accelerates the identification of potential drug candidates, improves design optimisation, and increases research efficiency. Additionally, ML in predictive analytics for pharmacy practice shows promising results, highlighting the need for further research and adoption to improve patient care (1). |
format |
Article |
author |
Zakaria, Yuslina |
author_facet |
Zakaria, Yuslina |
author_sort |
Zakaria, Yuslina |
title |
Revolutionising pharmacy through machine learning: the progress and perils / Yuslina Zakaria |
title_short |
Revolutionising pharmacy through machine learning: the progress and perils / Yuslina Zakaria |
title_full |
Revolutionising pharmacy through machine learning: the progress and perils / Yuslina Zakaria |
title_fullStr |
Revolutionising pharmacy through machine learning: the progress and perils / Yuslina Zakaria |
title_full_unstemmed |
Revolutionising pharmacy through machine learning: the progress and perils / Yuslina Zakaria |
title_sort |
revolutionising pharmacy through machine learning: the progress and perils / yuslina zakaria |
publisher |
Faculty of Pharmacy |
publishDate |
2024 |
url |
https://ir.uitm.edu.my/id/eprint/102828/1/102828.pdf https://ir.uitm.edu.my/id/eprint/102828/ |
_version_ |
1811598304431046656 |
score |
13.211869 |