Condensed memory networks

US11620506B2 · kind B2 · utility

Assignee

• KONINIKLIJKE PHILIPS N.V. · NL

Inventors

• Aaditya Prakash · Waltham, US
• Sheikh Sadid Al Hasan · Cambridge, US
• Oladimeji Feyisetan Farri · Yorktown Heights, US
• Kathy Mi Young Lee · Westford, US
• Vivek Varma Datla · Ashland, US
• Ashequl Qadir · Melrose, US
• Junyi Liu · Nanhu, CN

Key dates

• Filing date: Sep 18, 2017
• Grant date: Apr 4, 2023
• Expiry date: Aug 7, 2040

Classification

• Technology area (CPC G): Physics
• CPC primary: G16H50/20
• WIPO field: Computer technology
• WIPO sector: Electrical engineering

Abstract

Techniques are described herein for training and applying memory neural networks, such as “condensed” memory neural networks (“C-MemNN”) and/or “average” memory neural networks (“A-MemNN”). In various embodiments, the memory neural networks may be iteratively trained using training data in the form of free form clinical notes and clinical reference documents. In various embodiments, during each iteration of the training, a so-called “condensed” memory state may be generated and used as part of the next iteration. Once trained, a free form clinical note associated with a patient may be applied as input across the memory neural network to predict one or more diagnoses or outcomes of the patient.