TELADOC HEALTH, INC. (20240312476). AUTOMATED HEALTH CONDITION SCORING IN TELEHEALTH ENCOUNTERS simplified abstract

AUTOMATED HEALTH CONDITION SCORING IN TELEHEALTH ENCOUNTERS

Organization Name

TELADOC HEALTH, INC.

Inventor(s)

John O'donovan of Goleta CA (US)

Pushkar Shukla of Chicago IL (US)

Paul C. Mcelroy of Goleta CA (US)

Sushil Bharati of Goleta CA (US)

Marco Pinter of Santa Barbara CA (US)

AUTOMATED HEALTH CONDITION SCORING IN TELEHEALTH ENCOUNTERS - A simplified explanation of the abstract

This abstract first appeared for US patent application 20240312476 titled 'AUTOMATED HEALTH CONDITION SCORING IN TELEHEALTH ENCOUNTERS

The patent application describes a system for automated health condition scoring using artificial intelligence technology.

• Communication interface receives audio and video streams from a patient's location.
• Two AI detectors process the streams to determine likelihoods of health conditions.
• An AI scorer combines likelihoods to determine an overall health condition score.
• A display interface shows the health condition score to a physician.

Potential Applications: - Remote patient monitoring - Early detection of health conditions - Telemedicine consultations

Problems Solved: - Efficient health condition assessment - Remote monitoring without physical presence - Quick identification of potential health issues

Benefits: - Timely intervention for patients - Improved accuracy in health condition assessment - Enhanced communication between patients and healthcare providers

Commercial Applications: Title: "AI-Driven Automated Health Condition Scoring System" This technology can be used in telemedicine services, healthcare facilities, and remote patient monitoring systems, potentially revolutionizing the healthcare industry.

Questions about the technology: 1. How does the system ensure the privacy and security of patient data?

  - The system likely employs encryption and secure data storage protocols to protect patient information.

2. Can the AI accurately detect a wide range of health conditions?

  - The AI detectors are trained using machine learning to recognize various health conditions, improving accuracy over time.

Original Abstract Submitted

a system for automated health condition scoring includes at least one communication interface to receive an audio stream and a video stream from an endpoint in proximity to a patient, at least two different artificial intelligence (“ai”) detectors to respectively process one or both of the audio stream and the video stream using machine learning to automatically determine at least two respective likelihoods of the patient having a health condition, an ai scorer to combine the at least two respective likelihoods of the health condition using machine learning to automatically determine a health condition score representing an overall likelihood of the patient having the health condition, and a display interface that displays an indication of the health condition score to a physician.