Mark C Ruiz

US Patent:

20200285771, Sep 10, 2020

Filed:

Mar 5, 2019

Appl. No.:

16/292519

Inventors:

Abhishek Dey - Guahati, IN
Sam Tkach - Brooklyn NY, US
Mark Ruiz - San Francisco CA, US
Ray Rahman - San Francisco CA, US

International Classification:

G06F 21/62
G16H 30/20

Abstract:

A system and method for removing personally identifiable information (PII) from medical data and ensuring strict compliance with privacy laws and regulations. The PII removal tool removes, deletes or redacts sensitive personally identifiable information, which may comprise any health care data that may be linked to any individual. The system and method is preferably applied to medical data, images, video, or other electronic media captured from medical procedures, endoscopes, or arthroscopic surgery. Artificial intelligence powered software and models are applied to the medical data for the detection of PII comprising patient names, medical history, faces, account numbers, digital identities, biometric data, or other sensitive personal information which may be linked to an individual. Medical data is re-written without PII and the system generates metadata describing the deleted PII. Privacy law compliant medical data is normalized, stored hierarchically, and transmitted to third party storage systems for analysis with software models for medical insights, anatomical recognition, surgical metrics, patient outcome, diagnosis and medical payment and billing.

US Patent:

20190362022, Nov 28, 2019

Filed:

May 25, 2018

Appl. No.:

15/989205

Inventors:

Risto Haukioja - Palo Alto CA, US
Leon Mak - San Francisco CA, US
Mark Ruiz - San Francisco CA, US
Eli Sakov - San Francisco CA, US

International Classification:

G06F 17/30
G10L 15/04
G06F 3/0482

Abstract:

An audio labeling tool is described for rapidly and efficiently building a labeled data set preferably comprising audio files with annotations denoting speaker transcriptions, speaker identity, periods of silence, background noise, and speaker emotion labels. The tool provides a configurable user interface (UI) with keyboard shortcuts and menu items for streamlined user-guided markup of audio files with context specific labeling and transcription notes. Human audio file labelers will preferably leverage the labeling tool and configurable user interface and menu to rapidly annotate, validate, and build labeled data sets, at scale, of time sliced audio files. The audio labeling tool is preferably applied to audio files and provides an automated means for adding notations, markup, text transcription, and feature labeling to an audio waveform, spectrogram, or other audio data visualization domain for amplifying and highlighting audio feature details. Labeled audio data is preferably used to train computer models, develop pattern recognition algorithms, and neural networks for automated processing, pre-populating and labeling of significantly large audio data sets at scale.