Other

Epigenomics Ag

Therawis Diagnostics Gmbh

American Diagnostica, Inc.

Sekisui Diagnostics LLC

Biomedica Diagnostics Inc.

Harbeck, Nadia, Dr.

Kates, Ronald Dr.

Nadia Harbeck

Manfred Schmitt

Ronald Kates

Sabine Maier

John W Martens

Heinz Hoefler

John Foekens

Fabian Model

Ralf Lesche

Thomas Koenig

Almuth Marx

Inko Nimmrich

Dimo Dietrich

Thomas Hildmann

Oliver Hartmann

Peter Adorjan

Antje Kluth Lukas

Armin Schmitt

Tamas Rujan

Antje Kluth

Serenella Eppenberger-Castori

Vincent Vuaroqueaux

Volkmar Mueller

Frederique Spyratos

Ina Schwope

Maxime P Look

Gunter Weiss

Achim Plum

John Martens

Frédérique Spyratos

John A Foekens

Volkmar c/o Department Of Gynecology Müller

Thomas König

Heinz Höfler

Ronald E Kates

The present invention relates to methods for predicting the outcome of anthracycline treatment of cell proliferative disorder patients. This is achieved by determining the expression level of at least one gene selected from the group consisting of PITX2; TFF1 and PLAU. The invention also relates to sequences, oligonucleotides and antibodies which can be used within the described methods.

Markers for the prediction of outcome of anthracycline treatment

The present invention relates to modified and genomic sequences, to oligonucleotides and/or PNA-oligomers for detecting the cytosine methylation state of genomic DNA, as well as to a method for predicting the disease free survival and/or response of a subject with a cell proliferative disorder of the breast tissues, to endocrine treatment.

Methods for the prognosis of breast cancer

The present invention relates to modified and genomic sequences, to oligonucleotides and/or PNA-oligomers for detecting the cytosine methylation state of genomic DNA, as well as to a method for predicting the response of a subject with a cell proliferative disorder of the breast tissues, to endocrine treatment.

Method for determining risk of relapse of breast cancer following tamoxifen adjuvant therapy

The invention is directed to a method for training at least one learning-capable system comprising the steps of providing a predetermined training data set corresponding to a predetermined number of subjects comprising a predetermined input data set and a predetermined outcome data set, augmenting the input data set and/or the outcome data set, and training each learning-capable system using the augmented input data set and/or the augmented outcome data set.

Method for training a learning-capable system

The invention concerns a method for determining competing risks for objects following an initial event based on previously measured or otherwise objectifiable training data patterns, in which several signals obtained from a learning capable system are combined in an objective function in such a way that said learning capable system is rendered capable of detecting or forecasting the underlying probabilities of each of the said competing risks.

Method for determining competing risks

A method for training a neural network in order to optimize the structure of the neural network includes identifying and eliminating synapses that have no significant influence on the curve of the risk function. First and second sending neurons are selected that are connected to the same receiving neuron by respective first and second synapses. It is assumed that there is a correlation of response signals from the first and second sending neurons to the same receiving neuron. The first synapse is interrupted and a weight of the second synapse is adapted in its place. The output signals of the changed neural network are compared with the output signals of the unchanged neural network. If the comparison result does not exceed a predetermined level, the first synapse is eliminated, thereby simplifying the structure of the neural network.

Method for training a neural network

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Otterfing, Germany

Nadia Harbeck