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Ms-Technologies Gmbh

Kewei Chen

Eric M Reiman

Teresa Wu

Yuan-Ming Fleming Lure

Jing Li

Yi Su

Xiaonan Liu

David Weidman

A system and method for predicting mild cognitive impairment (MCI) related diagnosis and prognosis utilizing deep learning. More specifically, the system and method produce predictions of MCI conversions to Alzheimer's/dementia and prognosis related thereof. Using available medical imaging and non-imaging data a diagnosis and prognosis model is a deep learned model trained using transfer learning. An MCI-DAP server may then receive a request from a clinician to process predictions related to a target patient's diagnosis or prognosis. The target patient's medical data is retrieved and used to create a model for the target patient. Then details of the target patient's model and the diagnosis and prognosis model are compared, a prediction is generated, and the prediction is returned to the clinician. As new medical data becomes available it is fed into the respective model to improve accuracy and update predictions.

System and method for diagnostics and prognostics of mild cognitive impairment using deep learning

A method is disclosed to acquire imaging and non-imaging datasets from like objects. A linkage is found using a partial least squares (PLS) technique between imaging and non-imaging datasets. The linkage is then reduced to an expression of a single numerical assessment. The single numerical assessment is then used as an objective, quantified assessment of the differences and similarities between the objects. The data each dataset can be aspects of performance, physical characteristics, or measurements of appearance.

Methodologies linking patterns from multi-modality datasets

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Chandler, AZ, United States of America

Kewei Chen