Northwestern Memorial Healthcare

Mozziyar Etemadi

Michael Thompson

Jonathan Huang

Caitlin Teague

Matthew Wittbrodt

Eric Karl

Galal Galal

James Alex Heller

Systems and methods include techniques associated with one or more machine learning systems analyze, compare, and process one or both of model outputs or model inputs. Content verification may include generating content using a first trained machine learning system and then verifying the initial generation using one or more second trained machine learning systems, such as by generating content associated with a prompt, comparing output labels, or comparing output responsive to changing parameters. Additionally, data preparation may include image scaling and batching methods to improve machine learning outputs.

Assessment of clinical evaluations from machine learning systems

Approaches for analyzing an input image and providing one or more outputs related to the input image are provided. In accordance with an exemplary embodiment, an input image may be received and analyzed, using a trained machine learning model, to generate an inference related to the image. Based, at least in part, upon the generated inference, one or more reports related to the inference can be generated and provided for presentation on a user device. A user can interact with the report in a conversational manner with the computer system to generate additional reports or insights related to the input image.

Image analysis and insight generation

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Chicago, IL, United States of America

Mozziyar Etemadi