Research
Exploring AI in weight loss interventions and behavior methods.
Exercise guidance is also its strong point. It will design a step-by-step exercise plan based on the user's physical condition and athletic ability. For example, for users who lack a foundation in exercise, start with daily walking, gradually increase the number of steps, and then slowly introduce aerobic exercise a fixed number of times a week. As users adapt and gradually increase the intensity of exercise, efficient fat-burning exercises such as brisk walking interval training will also be added in due course. At the same time, they will also remind you to warm up and relax before and after exercise to avoid sports injuries. The AI intelligent body "Weight Loss π" launched by Shanzhen will regularly follow up on users' weight indicators, and urge users to control their diet, exercise on time, and adjust their weight loss plans in a timely manner through methods such as clocking in, taking photos, and pushing courses.
Natural language processing is the key to achieving smooth human-computer dialogue. It gives artificial intelligence the ability to understand human language, covering lexical analysis, syntactic analysis, semantic understanding and other aspects. For example, when a user expresses "I always want to eat high-calorie foods recently, and it's hard to lose weight", NLP technology can accurately identify the dietary temptations and weight loss problems faced by users, and conduct intent analysis to provide a basis for subsequent responses. At the same time, through sentiment analysis technology, it can also perceive the negative emotions in users' words so as to provide encouragement and support in time.
Innovative Weight Loss Solutions Through AI
We conduct research on weight loss interventions using AI, collaborating with medical institutions to address diverse user needs and improve health management through effective behavioral strategies.
Life-changing experience with Noom's AI.
Alex
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Machine learning and deep learning algorithms are the core of AI-based personalized weight loss programs. Prediction models are built by training a large amount of user weight loss data, including physical indicators, diet records, exercise data, and weight loss effects. Take the Qilu Xiangshou ENHIM weight management model AI weight loss doctor as an example. It is based on a large amount of obesity medical record data and multidisciplinary knowledge, and uses deep learning algorithms to continuously optimize the model, so that it can generate accurate personalized weight assessments and weight loss recommendations for patients within 3 minutes.
Some weight loss AIs have the function of food image recognition, which relies on computer vision technology. For example, in the “reduced order” weight management AI model, after users upload food pictures, computer vision technology quickly analyzes the type and quantity of food through image feature extraction, pattern recognition and other steps, and then calculates calories and nutrients, providing data support for diet management.
In terms of diet management, AI is similar to a smart butler. On the one hand, it collects real-time user diet information, whether it is actively input by the user or obtained through image recognition, and comprehensively analyzes the nutritional structure and calorie intake of the diet. On the other hand, it generates diet suggestions based on the user's weight loss goals and physical condition, such as recommending healthy recipes and reminding people to control their food intake. For example, for users who want to lose fat, it will be recommended to reduce carbohydrate intake and increase the proportion of protein.