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Yolov5-based dermatological non-prescription medicine selling method

An over-the-counter drug and dermatology technology, applied in the field of image recognition, can solve the problems of slow detection speed and low recognition accuracy, and achieve the effect of solving slow detection speed and low recognition accuracy

Pending Publication Date: 2021-08-24
XIAN UNIV OF TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Benefits of technology

This patented technology uses an XYZ system called YOLL-5 (a specialized computer program) trained on images collected from patients' skins during medical examinations or treatment procedures. It can accurately identify different types of skin diseases such as acne scars, warts, wrinkles, etc., without requiring manual analysis. By analyzing this data over time, we suggest recommendings about drug combinations that could help improve patient outcomes through faster diagnosis times.

Problems solved by technology

This patents describes methods available for treating certain conditions caused by excessive exposure to harmful chemical substances (such as sunlight) which may cause damage to sensitive areas like our eyesight. These techniques involve giving small amounts of these substance(especially when applied topically). Examples of commonly known products containing this type of ingredients includes oxybutynin gel, clay mineral oil solution, bacteriophage solutions, wax emulsion, eye drops with specific active agents, powders made up primarily of yeast cell walls, dyes called bleachers, quaternary ammonium salts, calcium salt, cyanides, carboxylic acid esterase enzyme preparations, antibiotic compositions, antihistonists, anesthetic lotions, moistenings, tonics, sponginess patches, among others.

Method used

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  • Yolov5-based dermatological non-prescription medicine selling method

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Embodiment Construction

[0033] The present invention will be described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0034] The present invention provides a yolov5-based dermatology over-the-counter drug sales method, as shown in Figure 1, comprising the following steps:

[0035] Step 1. Collect the original images of common skin diseases with a resolution of 2560×1920. There are a total of six common skin diseases, namely herpes, pustular acne, acne, dermatitis eczema, folliculitis and mosquito bites, and the collected skin diseases The original image is preprocessed to extract the characteristic values ​​of various skin diseases.

[0036] The main purpose of image preprocessing is to eliminate irrelevant information in the image, restore useful real information, enhance the detectability of relevant information and minimize data, thereby improving the reliability of feature extraction, image segmentation, matching and recognition. The image data in the d...

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PUM

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Abstract

The invention discloses a yolov5-based dermatological non-prescription medicine selling method, which comprises the following steps of: acquiring an original image of a skin disease, preprocessing, and extracting characteristic values of various skin diseases; carrying out manual labeling on the characteristic values by using data set labeling software labmeli to obtain skin disease category information and coordinate information; inputting the image into a yolov5 deep learning detection network and training the image; acquiring a picture of a diseased part of a patient, inputting the picture into a yolov5 detection network for detection, and judging the type of a corresponding skin disease; and linking the dermatosis types with the corresponding drugs by utilizing probability data association and displaying the dermatosis types and the corresponding drugs to the patient. According to the method, the to-be-detected skin disease picture is collected, the skin disease type is detected by using the yov5 deep learning algorithm, the detection result and the recommended medicine are connected by using the Apriori association algorithm, and the related medicine is pushed, so that the problems of low recognition precision and low detection speed caused by manual medicine selling in the prior art are solved.

Description

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Claims

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Application Information

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Owner XIAN UNIV OF TECH
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