1. Securing of clinical data for AI diagnosis
- Application of 5-step clinical verification process to secure reliability of clinical data
- Securing disease classification data with high reliability through prospective clinical research
- Maintenance of no loss of the original sound for each stage of transmission
2. AI lung/heart sound classification algorithm
- Determination of abnormalities in lung/heart sound and development of disease classification model
- Collection of disease data by Normal/abnormal lung/heart sound
- A lightweight deep learning model
3. Disease classification AI
- Artificial intelligence learning based on reliable clinical data
- Optimization of data preprocessing to improve the accuracy of AI diagnosis
- The calculation of probability for each disease by classifying the stethoscope data as Multi-task CNN Model
- Application of X-AI module → Presentation of the basis for judging the outcome of AI diagnosis (Improving reliability)
4. Skeeper AI
- Skeeper Edge AI an AIoT-based stethoscope solution, strengthening the security of stethoscope medical data through the intergration of edge computing and on-device AI.
- Edge AI technology plays the role of primary screening for cardiopulmonary health for both medical professionals and homecare(applied to Skeeper R1)
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AP
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Octa-core AP
Embedded Edge AI Solutions
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Mode Selection
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Camera
Stethoscope (Heart, Lung, Abdomen, and Others)
Data Transmission
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UI/UX
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Measurement, AI Analysis,
History, and Others
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Storage
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+30,000 Measure Data
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Wireless Communication
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Bluetooth, Wi-Fi