Waveform Ranking Using Teacher Data for Electrode Toxicity Evaluation
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Solution Overview
Problem
The current methods for selecting a target electrode based on microelectrode waveforms in toxicity evaluations are time-consuming and subjective, relying on sensory evaluation by humans, leading to varying accuracy due to evaluator experience.
Innovation Solution
An information processing apparatus and method using machine learning algorithms, such as clustering and neural networks, to analyze and select waveforms closest to an ideal waveform by comparing unknown waveforms with teacher data, enabling high-accuracy selection in a short time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If clinical trials are conducted to evaluate drug safety and efficacy, then reliable drug evaluation data can be obtained, but the process is time-consuming and expensive
Solution Approach 1:
The patent creates a virtual copy of the clinical trial system through a simulation apparatus that replicates patient characteristics, disease progression, and treatment responses. This virtual clinical trial allows repeated evaluations without conducting actual human trials, significantly reducing time and cost while maintaining data reliability through comprehensive computational modeling.
Solution Approach 2:
The system changes the fundamental parameters of clinical trial evaluation from physical human subjects to computational models. By adjusting parameters such as patient demographics, disease severity, and treatment protocols within the simulation environment, the system can rapidly evaluate multiple drug candidates under various conditions without the time constraints of real-world trials.
2Reliability
If multiple clinical trials are conducted to ensure comprehensive drug evaluation, then evaluation reliability improves, but evaluation cost increases
Solution Approach 1:
The simulation apparatus creates virtual replicas of clinical trial scenarios that can be repeatedly executed with different parameters. These virtual copies allow comprehensive evaluation of multiple drug candidates and treatment protocols simultaneously, eliminating the need to fund multiple physical clinical trials while maintaining thorough evaluation coverage.
Solution Approach 2:
The simulation system serves multiple evaluation functions simultaneously - it can assess different drug candidates, evaluate various dosing regimens, test combination therapies, and simulate different patient populations all within a single platform. This multi-functionality reduces the total resource consumption compared to conducting separate dedicated trials for each evaluation objective.
3Measurement precision
If actual clinical trials are performed to evaluate drug effects on patients, then real patient response data is obtained, but patient safety and ethical concerns arise
Solution Approach 1:
The system creates virtual patient models that replicate real patient characteristics, disease states, and treatment responses without exposing actual patients to experimental drugs. These virtual copies maintain measurement precision by incorporating comprehensive patient data and physiological models, while eliminating all patient safety risks associated with unproven drug administration.
Solution Approach 2:
The simulation apparatus acts as an intermediary between drug developers and actual patients. Instead of directly testing drugs on human subjects, the system first evaluates potential treatments on virtual patient models, filtering out unsafe or ineffective candidates before any human testing occurs. This intermediary layer preserves measurement accuracy while removing harmful factors.
Data Source
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AI summary
An information processing apparatus includes a processor. The processor acquires a plurality of unknown waveform data of which a determination result of superiority or inferiority based on similarity to an ideal waveform is unknown, performs a determination of the superiority or inferiority for each of the plurality of unknown waveform data based on a plurality of teacher waveform data to which the determination result of the superiority or inferiority is linked, and outputs the superiority or inferiority of the plurality of unknown waveform data in a comparable manner.