Artificial intelligence in cancer target identification and drug discovery
Artificial intelligence is an advanced method to identify novel anticancer targets and discover
novel drugs from biology networks because the networks can effectively preserve and …
novel drugs from biology networks because the networks can effectively preserve and …
Recommender systems in the healthcare domain: state-of-the-art and research issues
Nowadays, a vast amount of clinical data scattered across different sites on the Internet
hinders users from finding helpful information for their well-being improvement. Besides, the …
hinders users from finding helpful information for their well-being improvement. Besides, the …
[HTML][HTML] Role of artificial intelligence in patient safety outcomes: systematic literature review
A Choudhury, O Asan - JMIR medical informatics, 2020 - medinform.jmir.org
Background: Artificial intelligence (AI) provides opportunities to identify the health risks of
patients and thus influence patient safety outcomes. Objective: The purpose of this …
patients and thus influence patient safety outcomes. Objective: The purpose of this …
Identification of drug-side effect association via multiple information integration with centered kernel alignment
In medicine research, drug discovery aims to develop a drug to patients who will benefit from
it and try to avoid some side effects. However, the tradition experiment is time consuming …
it and try to avoid some side effects. However, the tradition experiment is time consuming …
A similarity-based method for prediction of drug side effects with heterogeneous information
X Zhao, L Chen, J Lu - Mathematical biosciences, 2018 - Elsevier
Drugs can produce intended therapeutic effects to treat different diseases. However, they
may also cause side effects at the same time. For an approved drug, it is best to detect all …
may also cause side effects at the same time. For an approved drug, it is best to detect all …
Predicting drug side effects by multi-label learning and ensemble learning
W Zhang, F Liu, L Luo, J Zhang - BMC bioinformatics, 2015 - Springer
Background Predicting drug side effects is an important topic in the drug discovery. Although
several machine learning methods have been proposed to predict side effects, there is still …
several machine learning methods have been proposed to predict side effects, there is still …
[HTML][HTML] Artificial intelligence in the field of pharmacy practice: A literature review
Artificial intelligence (AI) is a transformative technology used in various industrial sectors
including healthcare. In pharmacy practice, AI has the potential to significantly improve …
including healthcare. In pharmacy practice, AI has the potential to significantly improve …
Knowledge graph prediction of unknown adverse drug reactions and validation in electronic health records
Unknown adverse reactions to drugs available on the market present a significant health risk
and limit accurate judgement of the cost/benefit trade-off for medications. Machine learning …
and limit accurate judgement of the cost/benefit trade-off for medications. Machine learning …
Predicting potential side effects of drugs by recommender methods and ensemble learning
Drugs provide help and promise for human health, but they usually come with side effects.
Predicting side effects of drugs is a critical issue for the drug discovery. Although several …
Predicting side effects of drugs is a critical issue for the drug discovery. Although several …
Learning from the past and looking to the future: emerging perspectives for improving the treatment of psychiatric disorders
MJ Millan, GM Goodwin, A Meyer-Lindenberg… - European …, 2015 - Elsevier
Modern neuropsychopharmacology commenced in the 1950s with the serendipitous
discovery of first-generation antipsychotics and antidepressants which were therapeutically …
discovery of first-generation antipsychotics and antidepressants which were therapeutically …