000 01492 a2200397 4500
005 20250518081144.0
264 0 _c20200511
008 202005s 0 0 eng d
022 _a1091-6490
024 7 _a10.1073/pnas.1905355117
_2doi
040 _aNLM
_beng
_cNLM
100 1 _aHastings, Justine S
245 0 0 _aPredicting high-risk opioid prescriptions before they are given.
_h[electronic resource]
260 _bProceedings of the National Academy of Sciences of the United States of America
_c01 2020
300 _a1917-1923 p.
_bdigital
500 _aPublication Type: Journal Article; Research Support, Non-U.S. Gov't
650 0 4 _aAged
650 0 4 _aAlgorithms
650 0 4 _aAnalgesics, Opioid
_xtherapeutic use
650 0 4 _aDrug Prescriptions
_xstandards
650 0 4 _aFemale
650 0 4 _aHumans
650 0 4 _aMachine Learning
650 0 4 _aMale
650 0 4 _aMiddle Aged
650 0 4 _aOpioid-Related Disorders
_xdrug therapy
650 0 4 _aPractice Patterns, Physicians'
_xstandards
650 0 4 _aPredictive Value of Tests
650 0 4 _aPrescription Drug Misuse
_xprevention & control
650 0 4 _aRhode Island
_xepidemiology
650 0 4 _aRisk Assessment
_xmethods
700 1 _aHowison, Mark
700 1 _aInman, Sarah E
773 0 _tProceedings of the National Academy of Sciences of the United States of America
_gvol. 117
_gno. 4
_gp. 1917-1923
856 4 0 _uhttps://doi.org/10.1073/pnas.1905355117
_zAvailable from publisher's website
999 _c30518581
_d30518581