International Business Machines Corporation (20240331824). COGNITIVE CARDIAC AUSCULTATION BASED ON MULTIMODALITY AND CONTRASTIVE LEARNING simplified abstract
Contents
COGNITIVE CARDIAC AUSCULTATION BASED ON MULTIMODALITY AND CONTRASTIVE LEARNING
Organization Name
International Business Machines Corporation
Inventor(s)
Yuan Yuan Ding of Shanghai (CN)
COGNITIVE CARDIAC AUSCULTATION BASED ON MULTIMODALITY AND CONTRASTIVE LEARNING - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240331824 titled 'COGNITIVE CARDIAC AUSCULTATION BASED ON MULTIMODALITY AND CONTRASTIVE LEARNING
- Simplified Explanation:**
This patent application describes a method, computer program product, and computer system for predicting treatment options based on cardiac auscultation data. The data received includes text and audio data related to a patient's cardiac auscultation, which is then encoded as text vectors and audio vectors. A machine learning model determines diagnosis results based on the calculated distance between the text vectors and the audio vectors.
- Key Features and Innovation:**
- Predicting treatment options based on cardiac auscultation data
- Encoding text and audio data as vectors
- Calculating distance between text vectors and audio vectors
- Determining diagnosis results using a machine learning model
- Potential Applications:**
This technology can be applied in healthcare settings to assist healthcare professionals in making accurate and timely treatment decisions based on cardiac auscultation data.
- Problems Solved:**
- Providing a method to predict treatment options based on cardiac auscultation data
- Enhancing the accuracy and efficiency of diagnosis using machine learning models
- Benefits:**
- Improved treatment decision-making process
- Faster and more accurate diagnosis
- Enhanced patient care and outcomes
- Commercial Applications:**
- Title: Predictive Cardiac Auscultation Technology for Healthcare
- This technology can be utilized in hospitals, clinics, and other healthcare facilities to improve patient care and streamline the diagnostic process. It has the potential to be a valuable tool for healthcare providers looking to enhance their cardiac assessment capabilities.
- Questions about Predictive Cardiac Auscultation Technology:**
1. How does this technology improve the accuracy of treatment predictions based on cardiac auscultation data? 2. What are the potential implications of using machine learning models in diagnosing cardiac conditions?
Original Abstract Submitted
a method, computer program product, and computer system are provided for predicting treatment options based on cardiac auscultation data. text data and audio data corresponding to cardiac auscultation associated with a patient is received. the text data and the audio data are encoded as respective text vectors and audio vectors. a distance between the text vectors and the audio vectors is calculated. diagnosis results are determined by a machine learning model based on the calculated distance between the text vectors and the audio vectors.
