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Less popular antihypertensive drugs found to be safer

Less popular antihypertensive drugs found to be safer
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New yorkUnited statesGeorge hripcsakVivian beaumont allenColumbia university vagelos college of physiciansObservational health data scienceColumbia university vagelos collegeVivian beaumont allen professorபுதியது யார்க்ஒன்றுபட்டது மாநிலங்களில்விவியன் பியூமான்ட் ஆலன்அவதானிப்பு ஆரோக்கியம் தகவல்கள் அறிவியல்விவியன் பியூமான்ட் ஆலன் ப்ரொஃபெஸர்

Two types of blood pressure drugs provide equal benefits, but side effects differ

Two types of blood pressure drugs provide equal benefits, but side effects differ
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New yorkUnited statesColumbia universitySouth koreaBenton harborRuijun chenWillie lawrenceGeorge hripcsakEmily hendersonAmerican heart associationGeisinger medical centerColumbia university vagelos college of physiciansPresbyterian columbia university irving medical centerHealth equitySpectrum healthHigh blood pressure

Less popular antihypertensive drugs found to be safer option

Less popular antihypertensive drugs found to be safer option
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New yorkUnited statesGeorge hripcsakVivian beaumont allenColumbia university vagelos college of physiciansElectronic health records provideObservational health data scienceColumbia university vagelos collegeVivian beaumont allen professorபுதியது யார்க்ஒன்றுபட்டது மாநிலங்களில்விவியன் பியூமான்ட் ஆலன்அவதானிப்பு ஆரோக்கியம் தகவல்கள் அறிவியல்விவியன் பியூமான்ட் ஆலன் ப்ரொஃபெஸர்

More popular type of antihypertensive drugs causes slightly more side effects

More popular type of antihypertensive drugs causes slightly more side effects
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United statesGeorge hripcsakEmily hendersonVivian beaumont allenColumbia university vagelos college of physiciansObservational health data scienceColumbia university vagelos collegeVivian beaumont allen professorஒன்றுபட்டது மாநிலங்களில்எமிலி ஹென்டர்சன்விவியன் பியூமான்ட் ஆலன்அவதானிப்பு ஆரோக்கியம் தகவல்கள் அறிவியல்விவியன் பியூமான்ட் ஆலன் ப்ரொஃபெஸர்

Algorithm scours electronic health records to reveal hidden kidney disease

E-Mail NEW YORK, NY Diagnosing chronic kidney disease, which is often undetected until it causes irreversible damage, may soon become automated with a new algorithm that interprets data from electronic medical records. The algorithm, developed by researchers at Columbia University Vagelos College of Physicians and Surgeons, automatically scours a patient s electronic medical record for results of blood and urine tests and, using a mix of established equations and machine learning to process the data, can alert physicians to patients in the earliest stages of chronic kidney disease. A study of the algorithm was published in the journal npj Digital Medicine in April.

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