Abstract: In certain aspects of the present disclosure, a method for rapid informatics-based prognosis development includes receiving a consult request. The method includes selecting a study template configured to design a study to develop a consult output in response to the consult request. The method includes receiving a completed study template, including a completed field in the study template based on information from the consult request, the completed field comprising a variable provided in at least one of a timeframe field, a phenotype field, a cohort field, and a demographic field. The method includes obtaining cohort data based on the completed study template, the cohort data derived from a plurality of patient objects. The method includes generating the consult output based on the cohort data, the consult output comprising a result from an analysis of the cohort data according to a criteria and an instruction in the study template.

Abstract: The present invention provides a mechanism to use terminologies and ontologies for the purpose of indexing, annotating and semantically marking up existing collections of datasets. The invention further provides a system for incorporating terminologies, ontologies, and contextual annotation in specific domains, such as utilizing biomedical concept hierarchies in data analytics. The resulting rich structure supports specific mechanisms for data mining and machine learning.

Abstract: The present invention provides a mechanism to use terminologies and ontologies for the purpose of indexing, annotating and semantically marking up existing collections of datasets. The invention further provides a system for incorporating terminologies, ontologies, and contextual annotation in specific domains, such as utilizing biomedical concept hierarchies in data analytics. The resulting rich structure supports specific mechanisms for data mining and machine learning.

Abstract: The present invention provides a mechanism to use terminologies and ontologies for the purpose of indexing, annotating and semantically marking up existing collections of datasets. The invention further provides a system for incorporating terminologies, ontologies, and contextual annotation in specific domains, such as utilizing biomedical concept hierarchies in data analytics. The resulting rich structure supports specific mechanisms for data mining and machine learning.

Abstract: The present invention provides a mechanism to use terminologies and ontologies for the purpose of indexing, annotating and semantically marking up existing collections of datasets. The invention further provides a system for incorporating terminologies, ontologies, and contextual annotation in specific domains, such as utilizing biomedical concept hierarchies in data analytics. The resulting rich structure supports specific mechanisms for data mining and machine learning.

Abstract: Disclosed herein are methods for determining which embryos from a group of embryos are most likely to implant and develop as desired. In an embodiment of the present disclosure, one or more cells are biopsied from each of the embryos, and the genetic condition of those cells are determined. Within a group of embryos that each test positive for aneuploidy, the likelihood that each embryo contains euploid cells may be determined from the type of aneuploidy observed in the biopsied cells. This knowledge may be used to make a decision as to which embryos to transfer to a uterus. In an embodiment of the present disclosure, these determinations are made for the purpose of embryo selection in the context of in vitro fertilization.

Abstract: The system described herein enables clinicians and researchers to use aggregated genetic and phenotypic data from clinical trials and medical records to make the safest, most effective treatment decisions for each patient. This involves (i) the creation of a standardized ontology for genetic, phenotypic, clinical, pharmacokinetic, pharmacodynamic and other data sets, (ii) the creation of a translation engine to integrate heterogeneous data sets into a database using the standardized ontology, and (iii) the development of statistical methods to perform data validation and outcome prediction with the integrated data. The system is designed to interface with patient electronic medical records (EMRs) in hospitals and laboratories to extract a particular patient's relevant data. The system may also be used in the context of generating phenotypic predictions and enhanced medical laboratory reports for treating clinicians.