Nec corporation (20240161925). ELECTROCARDIOGRAM-BASED DIAGNOSIS MODEL LEARNING DEVICE, ELECTROCARDIOGRAM-BASED DIAGNOSIS MODEL LEARNING METHOD, AND STORAGE MEDIUM simplified abstract

ELECTROCARDIOGRAM-BASED DIAGNOSIS MODEL LEARNING DEVICE, ELECTROCARDIOGRAM-BASED DIAGNOSIS MODEL LEARNING METHOD, AND STORAGE MEDIUM

Organization Name

nec corporation

Inventor(s)

Yuan Luo of Tokyo (JP)

Mitsuru Noma of Tokyo (JP)

Osamu Hisamatsu of Tokyo (JP)

Kosuke Nishihara of Tokyo (JP)

Masahiro Kubo of Tokyo (JP)

Hiroaki Kataoka of Tokyo (JP)

Akihiko Shibano of Tokyo (JP)

ELECTROCARDIOGRAM-BASED DIAGNOSIS MODEL LEARNING DEVICE, ELECTROCARDIOGRAM-BASED DIAGNOSIS MODEL LEARNING METHOD, AND STORAGE MEDIUM - A simplified explanation of the abstract

This abstract first appeared for US patent application 20240161925 titled 'ELECTROCARDIOGRAM-BASED DIAGNOSIS MODEL LEARNING DEVICE, ELECTROCARDIOGRAM-BASED DIAGNOSIS MODEL LEARNING METHOD, AND STORAGE MEDIUM

Simplified Explanation

The patent application describes a learning device that utilizes electrocardiogram data to diagnose a target disease. Here is a simplified explanation of the abstract:

• First acquisition means acquires partial waveform of electrocardiogram data.
• Second acquisition means acquires an attention interval from the sequential waveform.
• Learning means trains a model to diagnose the target disease based on the partial waveform and attention interval.

1. 1. 1. Potential Applications of this Technology

- Remote monitoring of patients' heart health - Early detection of cardiovascular diseases

1. 1. 1. Problems Solved by this Technology

- Lack of efficient tools for diagnosing heart conditions - Limited access to specialized healthcare professionals

1. 1. 1. Benefits of this Technology

- Improved accuracy in diagnosing heart diseases - Timely intervention and treatment for patients

1. 1. 1. Potential Commercial Applications of this Technology
         1. Cardiovascular Disease Diagnosis and Monitoring Solutions

- Optimizing healthcare services for heart patients - Developing personalized treatment plans based on accurate diagnoses

1. 1. 1. Possible Prior Art

There are existing devices that use electrocardiogram data for diagnosing heart conditions, but the specific method described in this patent application may be novel.

1. 1. 1. 1. Unanswered Questions
         2. How does the learning device differentiate between various target diseases based on the electrocardiogram data?

The learning device uses a model trained on the partial waveform and attention interval to differentiate between target diseases. The specific algorithms and parameters used for this differentiation are not detailed in the abstract.

1. 1. 1. 1. What is the accuracy rate of the model in diagnosing the target disease?

The abstract does not mention the accuracy rate of the model in diagnosing the target disease. Further information on the validation and testing of the model's diagnostic capabilities would be needed to determine its effectiveness in real-world scenarios.

Original Abstract Submitted

a learning device x mainly includes a first acquisition means x, a second acquisition means x, and a learning means x. the first acquisition means x acquires a partial waveform of electrocardiogram data regarding an electrocardiogram of a subject. the second acquisition means x acquires an attention interval, which is used as a basis for a diagnosis of a target disease, in a sequential waveform of the electrocardiogram data. the learning means x trains a model configured to diagnose the target disease, based on the partial waveform and the attention interval.