Stephanie Lanius

Title: Stephanie Lanius: Innovator in Machine Learning and Healthcare

Introduction

Stephanie Lanius is a prominent inventor based in Cambridge, MA, known for her contributions to machine learning and healthcare technology. With a total of two patents to her name, she has made significant strides in developing innovative solutions that enhance data processing and risk assessment in medical contexts.

Latest Patents

One of her latest patents is titled "Word embedding for non-mutually exclusive categorical data." This invention involves a machine learning model that includes a categorical input feature with a defined set of values, alongside a plurality of non-categorical input features. The model features a word embedding layer designed to convert the categorical input into an output in a two-dimensional word space. Additionally, a machine learning network is configured to receive the output from the word embedding layer and the non-categorical input features, ultimately producing a machine learning model output.

Another notable patent is "Multilayer perceptron based network to identify baseline illness risk." This method focuses on training a baseline risk model by pre-processing input data through normalization of continuous variable inputs and generating one-hot input features for categorical variables. The process includes defining clean and dirty input data based on various patient conditions, segmenting the data, and training a machine learning model using the clean data subsets.

Career Highlights

Stephanie Lanius is currently employed at Koninklijke Philips Corporation N.V., where she continues to innovate in the field of healthcare technology. Her work is instrumental in advancing machine learning applications that can significantly impact patient care and medical research.

Collaborations

Some of her notable coworkers include Erina Ghosh and Emma Holdrich Schwager, who contribute to the collaborative environment that fosters innovation at Koninklijke Philips Corporation N.V.

Conclusion

Stephanie Lanius stands out as a key figure in the intersection of machine learning and healthcare, with her patents reflecting her commitment to improving medical data analysis and risk assessment. Her contributions are paving the way for future advancements in the field.