Abstract: Systems and methods are disclosed for automated industrial hygiene assessment and display comprising receiving sampling results for a stressor, such as a harmful environmental artifact in a physical environment; deriving one or more codes for the stressor from a digital record via an indexing module and/or from other data sources; generating a health effect rating (HER) based on the code; generating an exposure rating (ER) based on the sampling results; generating an uncertainty rating (UR) based on the sampling results; displaying, an interactive UIto facilitate approval or selection of at least one of the HER, the ER, or the UR; generating at least one of a risk rating (RR) or an information gathering priority rating (IGPR) based on a selection of the at least one of the HER, the ER, or the UR; and displaying via the interactive UI at least one of the RR or the IGPR.

Abstract: Systems and Methods are disclosed herein for automatically indexing multiple informational fields in digital data records, the method comprising: identifying, based on rules defining target information fields, for each target field of the target information fields, at least one page in a digital data record comprising content related to the target field; extracting, for each target field, from the identified at least one page, at least one portion of text comprising the content; feeding, for each target field, a pre-processed version of the at least one portion of text into a machine learning (ML) model, wherein the ML model is trained on the target field; determining, for each target field, via the ML model trained on the target field, at least one candidate text comprising the content; and extracting, for each target field, the at least one candidate text.

Abstract: Systems and methods are disclosed for automated industrial hygiene assessment and display comprising receiving sampling results for a stressor, such as a harmful environmental artifact in a physical environment; deriving one or more codes for the stressor from a digital record via an indexing module and/or from other data sources; generating a health effect rating (HER) based on the code; generating an exposure rating (ER) based on the sampling results; generating an uncertainty rating (UR) based on the sampling results; displaying, an interactive UI to facilitate approval or selection of at least one of the HER, the ER, or the UR; generating at least one of a risk rating (RR) or an information gathering priority rating (IGPR) based on a selection of the at least one of the HER, the ER, or the UR; and displaying via the interactive UI at least one of the RR or the IGPR.

Abstract: Systems and methods for automated indexing and extraction of information in digital documents are disclosed. A method may comprise identifying a page containing targeted information; inputting an image of the page into a visual machine learning network (visual ML), wherein the visual ML is trained to recognize text associated with the targeted information in an image; identifying by the visual ML, a section of the image that contains the targeted information; inputting the digital document, and coordinates of the section into an extraction module; and extracting the targeted information by the extraction module from the section.

Abstract: Systems and Methods are disclosed herein for automatically indexing multiple informational fields in digital data records, the method comprising: identifying, based on rules defining target information fields, for each target field of the target information fields, at least one page in a digital data record comprising content related to the target field; extracting, for each target field, from the identified at least one page, at least one portion of text comprising the content; feeding, for each target field, a pre-processed version of the at least one portion of text into a machine learning (ML) model, wherein the ML model is trained on the target field; determining, for each target field, via the ML model trained on the target field, at least one candidate text comprising the content; and extracting, for each target field, the at least one candidate text.

Abstract: Systems and methods for automated indexing and extraction of information in digital documents are disclosed. A method may comprise selecting a page number of a digital document to identify a page containing targeted information; inputting an image of the page into a visual machine learning network (visual ML), wherein the visual ML is trained to recognize text associated with the targeted information in an image; identifying by the visual ML, a section of the image that contains the targeted information; inputting the page number, the digital document, and coordinates of the section into an extraction module; and extracting the targeted information by the extraction module from the section.