000 01454 a2200361 4500
005 20250518012241.0
264 0 _c20190218
008 201902s 0 0 eng d
022 _a1091-6490
024 7 _a10.1073/pnas.1816459115
_2doi
040 _aNLM
_beng
_cNLM
100 1 _aSokolov, I
245 0 0 _aNoninvasive diagnostic imaging using machine-learning analysis of nanoresolution images of cell surfaces: Detection of bladder cancer.
_h[electronic resource]
260 _bProceedings of the National Academy of Sciences of the United States of America
_c12 2018
300 _a12920-12925 p.
_bdigital
500 _aPublication Type: Journal Article; Research Support, Non-U.S. Gov't; Research Support, U.S. Gov't, Non-P.H.S.
650 0 4 _aHumans
650 0 4 _aMachine Learning
650 0 4 _aMicroscopy, Atomic Force
_xmethods
650 0 4 _aSensitivity and Specificity
650 0 4 _aUrinary Bladder
_xdiagnostic imaging
650 0 4 _aUrinary Bladder Neoplasms
_xdiagnostic imaging
650 0 4 _aUrine
_xcytology
700 1 _aDokukin, M E
700 1 _aKalaparthi, V
700 1 _aMiljkovic, M
700 1 _aWang, A
700 1 _aSeigne, J D
700 1 _aGrivas, P
700 1 _aDemidenko, E
773 0 _tProceedings of the National Academy of Sciences of the United States of America
_gvol. 115
_gno. 51
_gp. 12920-12925
856 4 0 _uhttps://doi.org/10.1073/pnas.1816459115
_zAvailable from publisher's website
999 _c29123795
_d29123795