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An example graph of polypharmacy side effects derived from genomic and patient population data, protein–protein interactions, drug–protein targets, and drug–drug interactions encoded by 964 different polypharmacy side effects. The graph representation is used to develop Decagon. (credit: Marinka Zitnik et al./Bioinformatics)

Millions of people take up to five or more medications a day, but doctors have no idea what side effects might arise from adding another drug.*

Now, Stanford University computer scientists have developed a deep-learning system (a kind of AI modeled after the brain) called Decagon** that could help doctors make better decisions about which drugs to prescribe. It could also help researchers find better combinations of drugs to treat complex diseases.

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Finger pricks and daily insulin injections are currently the leading regimen for those with type 1 diabetes, a condition in which the body’s insulin producing cells beta cells are destroyed. And it’s not foolproof.

Patients can often face risks over overcorrecting their blood sugar levels, which can potentially lead to hypoglycemia – low blood sugar – and coma.

Insulin is responsible for regulating the amount of sugar in the blood, and dysfunctions with it can cause diabetes.

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In an experiment with global implications, Australian scientists have successfully wiped out more than 80% of disease-carrying mosquitoes in trial locations across north Queensland.

The experiment, conducted by scientists from the Commonwealth Scientific and Industrial Research Organization (CSIRO) and James Cook University (JCU), targeted Aedes aegypti mosquitoes, which spread deadly diseases such as dengue fever and Zika.

In JCU laboratories, researchers bred almost 20 million mosquitoes, infecting males with bacteria that made them sterile. Then, last summer, they released over three million of them in three towns on the Cassowary Coast.

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