SYSTEMS AND METHODS FOR AUTOMATED FEATURE-BASED ALERT TRIGGERING

SYSTEMS AND METHODS FOR AUTOMATED FEATURE-BASED ALERT TRIGGERING

Systems and methods for feature-based alert triggering are disclosed herein. The system can include memory including a model database containing a machine-learning algorithm. The system can include a user device that can receive inputs from a user; and at least one server. The at least one server ca...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Hauptverfasser: CASKEY, Michael, MCTAVISH, Thomas Scott, KUKARTSEV, Gennadiy, KNIF, Simcha, COLEMAN, Jennifer, LOVEJOY, David, ROUTH, Sumona, SAXENA, Ritu, ITELMAN, Ron, CARROLL, Stephen
Format: Patent
Sprache:eng ; fre ; ger
Schlagworte:
ALARM SYSTEMS
CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES
ORDER TELEGRAPHS
PHYSICS
SIGNALLING
SIGNALLING OR CALLING SYSTEMS
SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR
Online-Zugang:Volltext bestellen
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:Systems and methods for feature-based alert triggering are disclosed herein. The system can include memory including a model database containing a machine-learning algorithm. The system can include a user device that can receive inputs from a user; and at least one server. The at least one server can: receive electrical signals from the user device, the electrical signals corresponding to a plurality of user inputs provided to the user device; automatically generate input-based features from the received electrical signals; input the input-based features into the machine-learning algorithm; automatically and directly generate a risk prediction with the machine-learning algorithm from the input-based features; and generate and display an alert when the risk prediction exceeds a threshold value.