[et_pb_section fb_built=”1″ _builder_version=”4.9.0″ _module_preset=”default”][et_pb_row _builder_version=”4.9.0″ _module_preset=”default” custom_margin=”||0px||false|false” custom_padding=”||0px||false|false”][et_pb_column type=”4_4″ _builder_version=”4.9.0″ _module_preset=”default”][et_pb_text _builder_version=”4.9.0″ _module_preset=”default” hover_enabled=”0″ sticky_enabled=”0″]<\/p>\n
[\/et_pb_text][et_pb_text admin_label=”Text” _builder_version=”4.9.0″ _module_preset=”default” text_font_size=”22px” custom_margin=”||0px||false|false” custom_padding=”||0px||false|false” hover_enabled=”0″ sticky_enabled=”0″]<\/p>\n
We are continually working on adding new data modalities to AIR\u00b7MS as part of our goal of creating a rich, multi-model dataset. At this time, we offer the following datasets on the platform:<\/p>\n
[\/et_pb_text][\/et_pb_column][\/et_pb_row][et_pb_row _builder_version=”4.9.0″ _module_preset=”default”][et_pb_column type=”4_4″ _builder_version=”4.9.0″ _module_preset=”default”][et_pb_accordion icon_color=”#221F72″ admin_label=”Accordion” _builder_version=”4.9.0″ _module_preset=”default” custom_margin=”0px||||false|false” custom_padding=”0px||||false|false” hover_enabled=”0″ sticky_enabled=”0″][et_pb_accordion_item title=”Mount Sinai Data Warehouse” open=”on” icon_color=”#221F72″ _builder_version=”4.9.0″ _module_preset=”default” hover_enabled=”0″ border_radii=”on|3px|3px|3px|3px” border_color_all=”#221F72″ sticky_enabled=”0″]<\/p>\n
The\u202fMount Sinai Data Warehouse (MSDW)<\/a>\u202fdataset uses the\u202fOMOP Common Data Model<\/a> as a CDM. The data comprises\u202fclinical data extracted from Mount Sinai\u2019s Epic Caboodle database and other ancillary systems.<\/p>\n We offer both an identifiable and a de-identified version of the MSDW dataset in AIR\u00b7MS.<\/strong> In addition, many of the standard OMOP tables contain extension fields which contain data outside of the OMOP standard. Many of these additional attributes are based on data derived directly from EPIC (that is, codes used in EPIC rather than the standardized OMOP codes), or attributes not currently contained in the OMOP standard.<\/p>\n [\/et_pb_accordion_item][et_pb_accordion_item title=”Clinical Notes” _builder_version=”4.9.0″ _module_preset=”default” hover_enabled=”0″ border_radii=”on|3px|3px|3px|3px” border_color_all=”#221F72″ open=”off” sticky_enabled=”0″]Clinical notes in the form of unstructured data (progress notes, telephone encounters, nursing notes, procedures, etc.) extracted from the MSDW OMOP identifiable dataset have been loaded to AIR\u00b7MS and enabled for search using SAP HANA’s in-memory full-text search capabilities. This feature empowers the researcher to build patient cohorts based on terms contained in unstructured reports in seconds or even milliseconds! The researcher can further filter based on note type or an array of other clinical attributes.[\/et_pb_accordion_item][et_pb_accordion_item title=”Computational Pathology” icon_color=”#221F72″ _builder_version=”4.9.0″ _module_preset=”default” hover_enabled=”0″ border_radii=”on|3px|3px|3px|3px” border_color_all=”#221F72″ open=”off” sticky_enabled=”0″]The pathology metadata will aid researchers in the field of Computational Pathology<\/a>. Researchers will be able to build their patient cohort across data modalities, and subsequently apply\u00a0quantitative methods\u00a0for the analysis of digital microscopy slides relating the resulting statistical descriptors to patient outcomes.[\/et_pb_accordion_item][\/et_pb_accordion][et_pb_text admin_label=”Text” _builder_version=”4.9.0″ _module_preset=”default” custom_margin=”||0px||false|false” custom_padding=”||0px||false|false” hover_enabled=”0″ locked=”off” sticky_enabled=”0″]<\/p>\n Mount Sinai Health System users can access the AIR\u00b7MS Sharepoint for further access to current data modalities.<\/a><\/p>\n