'We have been engaged in the manufacturing of medical and health equipment for more than 20 years,' Mr. Lu recalled in his opening remarks. 'From the original mechanical weight scale to the current ultrasonic measurement equipment and large intelligent desktop Intelligent Health Check-up Kiosk, technology has continued to advance. But today, we stand at a new crossroads.' With the further advancement of the Healthy China strategy and people's growing demand for health management, simple data measurement can no longer meet market demand. Traditional health measurement equipment faces the triple challenges of intelligence, precision, and personalization. 'Our meeting today is to discuss how to integrate artificial intelligence, especially deep learning technology, into our products to create a new generation of intelligent health measurementCases.' Mr. Lu's speech clarified the goals of the meeting.
Thoughts from the meeting - Deep Learning: An internal technology collision full of useful information
Professor Yang, a technical engineer from Peking University, came to Lejia for technical training and guidance. Representatives from various departments from sales, research and development to after-sales and quality inspection gathered together, and the neural network structure diagram of deep learning was displayed on the large screen. 'In the past, our devices collected data and users saw numbers; in the future, our devices collect data and the system provides health insights. Professor Yang gave in-depth explanations and communication from the overall development process, the relationship between various types of AI learning to the concepts of deep learning networks, and 'the 'Examples of deep learning components' part of the PPT aroused heated discussion.
Technical Thoughts: When AI meets the 'hard core' of medical testing
The sharing session entered a heated discussion session - the 'Thinking' section of the PPT raised four sharp questions:
Regarding the loss of image information and spatial details, the sales department put forward the actual needs of customers: 'Many users have reported that our ultrasonic body shape analysis can be more accurate in identifying the distribution of muscles and fat.'
'The technical team admitted that the current convolution and pooling operations do lose some spatial information, but they demonstrated new deformable convolution and attention mechanisms Cases. The small target detection problem triggered cross-department brainstorming. The after-sales department shared on-site cases: there are challenges in the capture of subtle movements by baby scales and the identification of weak abnormal signals by medical examination equipment. 'Human doctors can notice these subtle changes based on experience, how can AI do it? 'The quality inspection department asked. The R&D team showed the direction they are exploring: 'We are studying a multi-scale attention mechanism combined with Transformer, so that the model can pay attention to the overall trend like an experienced doctor without missing any subtle anomalies. 'Professor Yang gave technical answers based on current problems and proposed Cases discussions.
Mr. Lu described the intelligent strategic path of Lejia Electronics: in the first stage, existing products will be added with AI auxiliary functions; in the second stage, intelligent health terminals that can be connected to the Internet will be developed; in the third stage, a complete personal health data ecosystem will be built. 'In the future, our devices will become intelligent portals for users' health data.' Mr. Tu added, 'These in-depth analyzed data, with user authorization, can safely serve personalized health management, early risk warning and even clinical decision support.'
Meeting summary
At the end of the meeting, Mr. Lu concluded: 'What we discussed today is not only a technology application, but also the strategic direction of enterprise development. Artificial intelligence is not to replace our existing products, but to amplify their value, expand their boundaries and be a partner to extend our capabilities.' From precision measurement to intelligent analysis, from single data to health insights, Henan Lejia Electronic Technology Co., Ltd. is steadily on the road of innovation integrating health technology and artificial intelligence. Representatives from various departments present gave affirmation. Everyone gained a lot from this training and technical exchange, made an in-depth summary, and provided strong support in the next work.
This whole-day technology sharing session is not so much an end point as it is a starting point - the starting point for Lejia Electronics' intelligent transformation and a new starting point for the evolution of health measurement equipment. In the development plan of Lejia Electronics, artificial intelligence is not a marketing gimmick, but a technical tool that actually enhances product value and improves user experience. When deep learning meets medical testing equipment, it changes not only the measurement accuracy, but also the entire paradigm of health management. When AI meets medical health, and when deep learning is integrated into daily measurements, a new era of more intelligent, accurate, and personalized health management is coming.
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