How to Use Machine Learning to Forecast Adverse Drug Reactions

When patients suffer unintended reactions to medicines, it can be both dangerous for the individual and costly to society. However, what if medical professionals could use machine learning to forecast adverse drug reactions (ADRs) and minimise risks to patients? ADRs are a huge concern within the healthcare industry, directly accounting for approximately <a href="https://www.sciencedirect.com/topics/medicine-and-dentistry/adverse-drug-reaction" rel="noopener ugc nofollow" target="_blank">5% of all hospital admissions</a> and estimated to be the <a href="https://www.sciencedirect.com/topics/medicine-and-dentistry/adverse-drug-reaction" rel="noopener ugc nofollow" target="_blank">sixth leading cause of death</a> worldwide. <a href="https://www.england.nhs.uk/healthcare-science/personalisedmedicine/" rel="noopener ugc nofollow" target="_blank">Personalised medicine is already a fast-developing trend,</a> but imagine if doctors could predict the likelihood of a patient suffering from an ADR before prescribing them drugs. <a href="https://towardsdatascience.com/how-to-use-machine-learning-to-forecast-adverse-drug-reactions-abc83ab91afd">Visit Now</a>