CONDENSED MEMORY NETWORKS

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...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Hauptverfasser:	FARRI, Oladimeji Feyisetan, AL HASAN, Sheikh Sadid, LEE, Kathy Mi Young, DATLA, Vivek Varma, QADIR, Ashequl, LIU, Junyi, PRAKASH, Aaditya
Format:	Patent
Sprache:	eng
Schlagworte:	CALCULATING COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING COUNTING HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATIONTECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING ORPROCESSING OF MEDICAL OR HEALTHCARE DATA INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTEDFOR SPECIFIC APPLICATION FIELDS PHYSICS
Online-Zugang:	Volltext bestellen
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Beschreibung
Zusammenfassung:	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.