Background:
In the field of personalized health, it is often difficult for individuals to
obtain professional knowledge to solve their practical problems timely and accurately. While there
are some applications that can get targeted information, they often fail to function properly in nonideal
environments, and they cannot achieve precise answers to individual users. Therefore, how to
establish an information capture model based on big data and combine it with intelligent search is
an important issue in the field of personalized health.
Objective:
This paper starts with the information acquisition and intelligent recommendation in the
field of personalized health, and proposes a natural scene information acquisition and analysis
model based on deep learning, focusing on improving the recognition rate of text in natural scenes
and achieving targeted smart search to allow users to get more accurate personalized health advice.
Methods:
In this model, natural scene information is processed from four aspects: targeted big data
collection and search, connected text proposal network text detection algorithm and projectionbased
text segmentation, capsule network text recognition and result analysis. The model reduces
recognition bias due to problems such as special filming conditions and photographic techniques
by using deep learning algorithms. At the same time, the data mining has also improved the pertinence
of the results analysis.
Conclusion:
This model combines deep learning and data mining methods to obtain intelligent solutions
at a professional level by uploading target information images in non-ideal environments,
and is suitable for accurate analysis of problems in personalized health area.
Results:
The proposed model is applied to analyze the user's nutrient intake requirements. The results
show that the method achieves 83% prediction accuracy on the nutrient composition table dataset,
and its performance is better than current convolutional neural network applications. And the
model can get accurate personalized data to provide users with dietary advice.