Preventive Medicine Sector
Introduction
The API /virtualbot/analisys_image_report/ is a tool designed to support healthcare professionals in the field of Preventive Medicine. This API processes patient medical images, combining them with their clinical history (if provided), and generates personalized recommendations based on the findings from the images and the information provided. The goal is to promote healthy habits and disease prevention by helping identify risk factors and guiding lifestyle changes. It is important to note that the API does not store images or clinical history, ensuring patient data privacy and confidentiality.
Functioning of the API /virtualbot/analisys_image_report/
Endpoint: POST /virtualbot/analisys_image_report/
Input Parameters:
- Patient Images: A .zip file containing the images to be analyzed, such as X-rays, ultrasounds, CT scans, etc.
- Patient Data: Basic information in JSON format that may include:
– Name
– Age
– Gender
– Medical history (if available)
- User Instructions: A JSON specifying the type of analysis requested for the images. For example, if it is desired to identify risk factors such as fatty liver or calcifications in arteries.
Example Request:
{
"user": "doctor@example.com",
"type": "preventive_medicine",
"analysis": "Analyze the images to identify risk factors and generate preventive recommendations."
}
Example Patient Data:
{
"name": "Pedro Gómez",
"age": "50",
"gender": "Male",
"medical_history": "Family history of cardiovascular diseases, sedentary, occasional smoker."
}
Process:
- The API receives the .zip file with the images and patient data.
- It uses the clinical history to contextualize the analysis (although it is not mandatory to provide it).
- It analyzes each image for risk factors:
– Identification of fatty liver, calcifications in arteries, elevated visceral fat levels, signs of incipient osteoporosis, among others.
- It generates a detailed report of the findings for each image.
- It provides preventive recommendations based on the findings and the patient’s history, such as dietary changes, increased physical activity, quitting smoking, among others.
Output:
A JSON report detailing the findings by image and offering personalized preventive recommendations.
Example JSON Response:
{
"diagnosis": {
"image_1": "Moderate hepatic steatosis (fatty liver) observed.",
"image_2": "Presence of calcifications in coronary arteries, indicative of cardiovascular risk.",
"recommendations": [
"Adopt a balanced diet low in saturated fats and sugars.",
"Incorporate regular physical activity of at least 30 minutes a day, five times a week.",
"Quit smoking to reduce cardiovascular risk.",
"Consult a cardiologist for further evaluation."
]
}
}
Applications in Preventive Medicine
- Identification of Risk Factors in Images:
– Description: The API analyzes medical images to identify risk factors such as fatty liver, calcifications in arteries, reduced bone density, excessive visceral fat, among others.
– Benefit: Allows early detection of conditions that may lead to chronic diseases, facilitating timely preventive interventions.
- Generation of Preventive Recommendations:
– Description: Based on the findings and clinical history, the API generates personalized recommendations aimed at prevention, such as dietary changes, increased physical activity, quitting smoking, among others.
– Benefit: Provides the patient and healthcare professional with a clear guide to implement lifestyle changes that reduce risks.
- Guidance on Lifestyle Changes:
– Description: The API suggests concrete actions to improve the patient’s health, such as exercise programs, specific diets, stress management, among others.
– Benefit: Helps the patient understand the importance of the proposed changes and how to implement them, increasing adherence to recommendations.
- Monitoring and Preventive Follow-Up:
– Description: Facilitates patient follow-up by generating reports that can be compared over time to assess the effectiveness of preventive interventions.
– Benefit: Allows the healthcare professional to adjust recommendations based on the patient’s progress, improving long-term outcomes.
Practical Examples of API Use
Example 1: Cardiovascular Disease Prevention
Request:
– Instructions: “Analyze the images to identify signs of cardiovascular risk and generate preventive recommendations.”
Patient Data:
{
"name": "Sofía Martínez",
"age": "55",
"gender": "Female",
"medical_history": "Controlled hypertension, sedentary lifestyle."
}
API Response:
{
"diagnosis": {
"image_1": "Calcifications in coronary arteries detected, indicating increased risk of cardiovascular disease.",
"recommendations": [
"Start a regular physical activity program under medical supervision.",
"Adopt a Mediterranean diet rich in fruits, vegetables, and healthy fats.",
"Periodically monitor cholesterol and blood pressure levels.",
"Consult with a cardiologist for evaluation and management."
]
}
}
Example 2: Detection of Incipient Osteoporosis
Request:
– Instructions: “Analyze the images to assess bone density and provide recommendations.”
Patient Data:
{
"name": "Miguel Rodríguez",
"age": "65",
"gender": "Male",
"medical_history": "No relevant history, occasional joint pain."
}
API Response:
{
"diagnosis": {
"image_1": "Bone density is decreased, suggesting osteopenia.",
"recommendations": [
"Increase intake of calcium and vitamin D.",
"Perform resistance and muscle-strengthening exercises.",
"Avoid excessive alcohol and tobacco consumption.",
"Schedule a bone density scan for detailed evaluation."
]
}
}
Example 3: Prevention of Type 2 Diabetes
Request:
– Instructions: “Analyze the images and history to identify the risk of type 2 diabetes and suggest preventive measures.”
Patient Data:
{
"name": "Laura Sánchez",
"age": "40",
"gender": "Female",
"medical_history": "Overweight, family history of diabetes."
}
API Response:
{
"diagnosis": {
"image_1": "Significant visceral fat accumulation observed.",
"recommendations": [
"Implement a weight loss plan under nutritional supervision.",
"Increase physical activity, combining aerobic and strength exercises.",
"Regularly monitor blood glucose levels.",
"Educate on healthy eating and stress management."
]
}
}
Advantages of Using the API in Preventive Medicine
- Early Detection of Risk Factors:
– Allows identification of health conditions that could lead to chronic diseases, facilitating timely preventive interventions.
- Personalized Recommendations:
– Offers suggestions tailored to the patient, considering their individual characteristics and clinical context.
- Patient Empowerment:
– By providing clear information and concrete actions, the patient becomes more involved in their care and makes informed decisions.
- Optimization of Healthcare Professional Time:
– Automates part of the analysis process and generation of recommendations, allowing the professional to focus on direct patient care.
- Does Not Store Sensitive Information:
– Ensures privacy and confidentiality of patient data, as it does not store images or personal data.
- Promotion of Healthy Habits:
– Encourages positive lifestyle changes, contributing to improved overall health and reducing the incidence of preventable diseases.
Summary
The API /virtualbot/analisys_image_report/ is an innovative tool for the Preventive Medicine sector, helping healthcare professionals identify risk factors and generate personalized recommendations based on medical image findings and the patient’s clinical history. Its implementation facilitates early detection of conditions that may lead to chronic diseases, promoting preventive interventions and fostering healthy habits. By combining advanced technology with a patient-centered approach, this API significantly contributes to improving health and well-bein
