Prescription: Issue No. 7 (July 2024)
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...
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Faculty of Pharmacy, Universiti Teknologi MARA, Kampus Puncak Alam
2024
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Online Access: | https://ir.uitm.edu.my/id/eprint/101433/1/101433.pdf https://ir.uitm.edu.my/id/eprint/101433/ |
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my.uitm.ir.1014332024-09-02T04:56:31Z https://ir.uitm.edu.my/id/eprint/101433/ Prescription: Issue No. 7 (July 2024) UiTM, Faculty of Pharmacy Pharmaceutical ethics Pharmacopoeias 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, Universiti Teknologi MARA, Kampus Puncak Alam 2024-07 Monograph NonPeerReviewed text en https://ir.uitm.edu.my/id/eprint/101433/1/101433.pdf Prescription: Issue No. 7 (July 2024). (2024) Bulletin. Faculty of Pharmacy, Universiti Teknologi MARA, Kampus Puncak Alam. (Unpublished) |
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Pharmaceutical ethics Pharmacopoeias Pharmaceutical technology UiTM, Faculty of Pharmacy Prescription: Issue No. 7 (July 2024) |
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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). |
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UiTM, Faculty of Pharmacy |
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UiTM, Faculty of Pharmacy |
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UiTM, Faculty of Pharmacy |
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Prescription: Issue No. 7 (July 2024) |
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Prescription: Issue No. 7 (July 2024) |
title_full |
Prescription: Issue No. 7 (July 2024) |
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Prescription: Issue No. 7 (July 2024) |
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Prescription: Issue No. 7 (July 2024) |
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prescription: issue no. 7 (july 2024) |
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Faculty of Pharmacy, Universiti Teknologi MARA, Kampus Puncak Alam |
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2024 |
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https://ir.uitm.edu.my/id/eprint/101433/1/101433.pdf https://ir.uitm.edu.my/id/eprint/101433/ |
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