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Student project on understanding emerging diseases via internet searches


You’re not feeling well so you open a search engine and type: fever, dry cough, hoping to find hints of what you may have. A handful of days later, you’re feeling worse, and you type in: trouble breathing. It turns out you’re not the only one who’s doing this, and a Harvard senior’s research project suggests that tracking the results of all those searches can tell us something about the progression of a new disease in individuals and through a population.
Tina Lu, a Leverett House computer science concentrator, analyzed search engine data from Google Trends going back to the beginning of the coronavirus pandemic to see how well symptom searches in 32 countries on six continents matched the clinical symptoms of COVID-19 and whether the number of searches served as a harbinger of rising incidence of cases. ....

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'Trending' doctors' notes could help hospitals predict COVID-19 surges


A new study, published today in
Nature Digital Medicine, found that natural language processing (NLP) of information routinely recorded by doctors - as part of patients electronic health records - reveal vital trends that could help clinical teams forecast and plan for surges in patients.
The researchers from King s College London, King s College Hospital NHS Foundation Trust (KCH), and Guy s and St Thomas Hospital NHS Foundation Trust (GSTT), used NLP algorithms to translate the electronic notes made by doctors into a standardised, structured set of medical terms that could be analysed by a computer.
Tracking trends in patients
In the same way social media posts can be tracked and aggregated by hashtags , the researchers detected words or phrases that were trending in electronic health records at KCH and GSTT, during key stages of the COVID-19 pandemic last year. For instance, they tracked the number of patient records containing keywords for symptomati ....

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