Siemens Corporation

Siemens Aktiengesellschaft

Siemens Medical Solutions USA, Inc.

Daniel Fasulo

Lu-yong Wang

Dorin Comaniciu

Bogdan Georgescu

Xiaoguang Lu

Zhuowen Tu

Lance Palmer

Gayle M Wittenberg

Lujia Chen

A method for generating classifiers for identifying neuropsychiatric disease includes acquiring functional neuroimaging data. The acquired functional neuroimaging data may be registered to an atlas of the brain. A discriminative mask is generated based on the registered functional neuroimaging data and the generated discriminative mask is applied to the registered functional neuroimaging data. One or more classifiers are generated for identifying neuropsychiatric disease based on the masked functional neuroimaging data. The accuracy of the generated classifiers may be verified. The generated classifiers may then be used to identify neuropsychiatric disease.

Method for developing test for neuropsychiatric disease

Methods and systems for identifying a primer pair for polymerase chain reaction specific to one or more target genomes. Methods and systems of the present disclosure can be used to identify primers that can distinguish between target genomes and closely related non-target genomes.

Methods and systems for identifying PCR primers specific to one or more target genomes

A program storage device is provided readable by machine, tangibly embodying a program of instructions executable by the machine to perform method steps for classification of biological tissue by gene expression profiling. The method steps include providing a training set of gene expression profiles of known tissue samples, providing a first-layer strong classifier of the known tissue samples by combining weak classifiers using boosting, creating two sample sets based on the first classifier, populating the two sample sets with a next-layer of classifiers based on a previous-layer classifier, organizing the classifiers in a tree data structure, and outputting the tree data structure as a probabilistic boosting tree classifier for tissue sample classification and disease subtype discovery. A multi-class diagnosis problem is transformed to a two-class diagnosis process by finding an optimal feature and dividing the multi-class problem into two-classes.

Joint classification and subtype discovery in tumor diagnosis by gene expression profiling

A system for providing medical decision support for diagnosis and treatment of disease comprises a medical knowledge database comprising medical information, the medical information including probabilities of disease outcomes for a disease of interest, a memory device for storing a program, a processor in communication with the memory device, the processor operative with the program to obtain patient information and in vitro test results for a patient, and automatically generate a recommendation for a medical test based on a combination of the patient information, the in vitro test results, and medical information from the medical knowledge database.

Systems and method for integrative medical decision support

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Titusville, NJ, United States of America

Daniel Fasulo