AI Chatbot Smoking Cessation System with Biomarker Validation
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Solution Overview
Problem
Current smoking cessation therapies face challenges due to limited access to health professionals and inaccurate self-reported data, leading to low long-term success rates as patients often relapse due to unaddressed psychological dependence and delayed detection of smoking reinstatement.
Innovation Solution
A system that uses a computer-readable medium to receive patient reports and biomarker concentration measurements, determining consistency between the two to provide tailored smoking cessation therapy, ensuring timely and appropriate intervention through a network of devices and servers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If self-reported data is used for smoking cessation therapy, then ease of operation is improved, but measurement precision deteriorates
Solution Approach 1:
The patent introduces an AI-based chatbot as an intermediary between the patient and the therapy system. The chatbot collects self-reported data through natural conversation, maintaining ease of operation, while applying consistency checks and cross-validation techniques to improve measurement precision by detecting discrepancies in patient reports.
Solution Approach 2:
The system implements feedback mechanisms where the AI chatbot analyzes self-reported data for consistency, provides immediate feedback to patients about detected discrepancies, and adjusts therapy recommendations based on validated information. This feedback loop improves measurement precision without compromising the ease of self-reporting.
2Loss of time
If outpatient service frequency is limited, then loss of time for patients is reduced, but reliability deteriorates
Solution Approach 1:
The patent implements a self-service monitoring system where patients use an AI chatbot and mobile application to self-report smoking status, receive real-time feedback, and get therapy recommendations without requiring frequent outpatient visits. This maintains reliability by providing continuous monitoring while reducing the time loss associated with multiple hospital visits.
Solution Approach 2:
The system enables continuous monitoring and support through the AI chatbot available 24/7 via mobile devices, replacing intermittent outpatient visits with continuous digital support. This maintains reliability by providing ongoing therapy and detection while eliminating the time loss of traveling to and waiting at outpatient clinics.
3Loss of time
If detection interval is extended, then loss of time for healthcare system is reduced, but measurement precision deteriorates
Solution Approach 1:
The patent implements preliminary detection mechanisms where the AI chatbot continuously analyzes patient reports in real-time, performing preliminary consistency checks and anomaly detection. When potential relapse is detected, the system immediately alerts healthcare providers, enabling timely intervention without requiring extended detection intervals or frequent outpatient visits.
4Ease of operation
If pharmacological therapy alone is used, then ease of operation is improved, but reliability deteriorates
Solution Approach 1:
The patent merges pharmacological therapy with AI-based behavioral monitoring and support. The system combines medication management with real-time data collection, consistency analysis, and personalized therapy recommendations, creating an integrated approach that maintains ease of operation while significantly improving reliability through multi-modal intervention.
Data Source
AI summary
A non-transitory computer-readable medium stores a program designed to be used for a patient attempting to quit smoking. The program causes a computer to execute: receiving report information input by the patient and indicative of the presence or absence of smoking by the patient; receiving a biomarker concentration measurement value measured from a biological sample of the patient by a biomarker concentration meter for measuring a biomarker concentration indicative of a smoking state; based on the received biomarker concentration measurement value and a biomarker concentration reference value, determining consistency between the biomarker concentration measurement value and the report information; based on a result of the consistency determination, generating smoking cessation therapy information for smoking cessation therapy to be performed for the patient; and transmitting the generated smoking cessation therapy information to a patient-side device.