20240055092. INTELLIGENT TELEHEALTH PLATFORM USING DAYPART FEEDBACK simplified abstract (EO Care, Inc.)

INTELLIGENT TELEHEALTH PLATFORM USING DAYPART FEEDBACK

Organization Name

EO Care, Inc.

Inventor(s)

David C. Batista of Brookline MA (US)

Stacey Batista of Brookline MA (US)

Benjamin P. Caplan of Needham MA (US)

Sean J. Collins of Wellesley MA (US)

Birch Norton of Ipswich MA (US)

Kristen P. Parton of Medfield MA (US)

Christine R. Pillsbury of Danvers MA (US)

Geordie Mcclelland of Cambridge MA (US)

INTELLIGENT TELEHEALTH PLATFORM USING DAYPART FEEDBACK - A simplified explanation of the abstract

This abstract first appeared for US patent application 20240055092 titled 'INTELLIGENT TELEHEALTH PLATFORM USING DAYPART FEEDBACK

Simplified Explanation

The patent application describes a system and method for using an intelligent telehealth platform to generate a recommended treatment plan based on daypart feedback to treat a malady of a user.

• The method involves obtaining a user profile dataset that includes user goals for different dayparts of the day.
• Treatment plans are generated based on the user dataset and a machine learning model trained to predict cannabis treatment responses.
• Each treatment plan involves using cannabis products during specific dayparts of the day.
• The treatment plans are transmitted to a client device for implementation.

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1. 1. 1. Potential Applications

• Telehealth platforms
• Personalized treatment plans
• Cannabis-based treatments

1. 1. 1. Problems Solved

• Providing personalized treatment recommendations
• Optimizing treatment effectiveness based on daypart feedback
• Enhancing user experience and engagement with telehealth platforms

1. 1. 1. Benefits

• Improved treatment outcomes
• Tailored treatment plans for individual users
• Enhanced user satisfaction and engagement with telehealth services

Original Abstract Submitted

a system and method of using an intelligent telehealth platform to generate a recommended treatment plan based on daypart feedback to treat a malady of a user. the method includes obtaining a user profile dataset of a user. the user profile dataset includes a plurality of user goals for a plurality of dayparts of a day, each daypart of the plurality of dayparts is respectively associated with one or more user goals of the plurality of user goals. the method includes generating a plurality of treatment plans to treat a malady of the user based on the user dataset and a machine learning model trained to predict cannabis treatment responses, each treatment plan is for using one or more cannabis products during a respective daypart of the plurality of dayparts of the day. the method includes transmitting the plurality of treatment plans to a client device.