Abstract: The present specification relates to a delayed fluorescence compound represented by chemical formula 1 and an organic light-emitting device comprising same, and achieves delayed fluorescence light sensitive hyperfluorescence properties by the use of a compound that exhibits deep blue properties and has a low singlet-triplet energy difference, and a fluorescence compound which, relative to conventional delayed fluorescence material, exhibits deep blue properties, has a narrow half-width, and has excellent color purity.

Abstract: A method, a computing system and a computer program product are provided. A model is generated and trained. The model is based on clinical data with outcomes from clinically-defined hierarchical metadata in a selected level of clinically-defined hierarchical metadata serving as an initial set of prediction targets. A score is determined for each of the prediction targets based on the generated model and the set of evaluation factors. The set of prediction targets, the generated model, and the scores for the set of prediction targets are updated until the updated scores for the updated set of prediction targets satisfy acceptance criteria. The updated generated model, using the updated set of prediction targets, is applied to predict one of a set of updated prediction targets of mutually exclusive outcome categories.

Abstract: Embodiments of the present invention disclose a method, a computer program product, and a computer system for enriching data. A computer receives a limited dataset and a target insight. In addition, the computer identifies an applicable richer dataset and determines a population relatedness between the limited dataset and the applicable richer dataset. Moreover, the computer calculates estimators of features using the richer dataset as well as calculates estimators for features using the limited dataset. The computer then updates the estimators of the limited dataset using estimators of the richer dataset and evaluates the updated estimators. Lastly, the computer provides a data collection recommendation as it relates to the limited dataset based on the evaluation.

Abstract: A computer system generates and manages clinical studies. A first collection of clinical documents is analyzed to extract clinical study goals and corresponding clinical study design components. A second collection of documents is analyzed to extract value sets indicating a mapping between clinical concepts and data elements of clinical information. The extracted clinical study design information and value sets are stored in a hierarchical structure within a repository that relates the clinical study goals, design components, concepts, and the data elements. A new clinical study is generated for a desired clinical study goal based on pattern recognition applied to the extracted clinical study design information and value sets in the repository using the repository. Embodiments of the present invention further include a method and program product for generating and managing clinical studies in substantially the same manner described above.

Abstract: Systems and computer-implemented methods for analysis of medical literature to assemble synthetic cohorts are provided. In various embodiments, a plurality of literature sources relating to a medical condition are retrieved. The plurality of literature sources comprise published observational studies. A first plurality of features is extracted from the plurality of literature sources. A subpopulation is defined based on the first plurality of features. An effectiveness of a treatment within the subpopulation is predicted based on the plurality of features. A plurality of electronic medical records is retrieved. The effectiveness of the treatment is validated against the plurality of electronic medical records.

Abstract: Embodiments of the present invention disclose a method, a computer program product, and a computer system for enriching data. A computer receives a limited dataset and a target insight. In addition, the computer identifies an applicable richer dataset and determines a population relatedness between the limited dataset and the applicable richer dataset. Moreover, the computer calculates estimators of features using the richer dataset as well as calculates estimators for features using the limited dataset. The computer then updates the estimators of the limited dataset using estimators of the richer dataset and evaluates the updated estimators. Lastly, the computer provides a data collection recommendation as it relates to the limited dataset based on the evaluation.

Abstract: A method, a computing system and a computer program product are provided. A model is generated and trained. The model is based on clinical data with outcomes from clinically-defined hierarchical metadata in a selected level of clinically-defined hierarchical metadata serving as an initial set of prediction targets. A score is determined for each of the prediction targets based on the generated model and the set of evaluation factors. The set of prediction targets, the generated model, and the scores for the set of prediction targets are updated until the updated scores for the updated set of prediction targets satisfy acceptance criteria. The updated generated model, using the updated set of prediction targets, is applied to predict one of a set of updated prediction targets of mutually exclusive outcome categories.

Abstract: The present invention provides methods for diagnosis and prognosis of cancer stem cells (CSC) using expression analysis of one or more groups of genes, and a combination of expression analysis from a biological sample from the subject. The methods of the invention provide a method for accuracy detecting cancer stem cells in a population of cancer cells. The invention also provides methods and kits for diagnosis and prognosis of cancer in a subject using cancer stem cell biomarker expression analysis.