Part of the series

Several example codes

~2 min read • Updated Sep 29, 2025

Program Overview

This Python program models a simplified decision-making system that selects the best surgical method based on a predefined treatment plan.
The user provides their risk tolerance and treatment priority (e.g., recovery time or effectiveness), and the program recommends the most suitable surgical option.


Python Code:


# Define available surgical options
surgical_options = {
    "minimally_invasive": {"risk": 2, "recovery": 5, "effectiveness": 7},
    "open_surgery": {"risk": 5, "recovery": 10, "effectiveness": 9},
    "robotic_assisted": {"risk": 3, "recovery": 6, "effectiveness": 8}
}

# Get patient preferences
risk_tolerance = int(input("Maximum acceptable risk (1 to 5): "))
priority = input("What is your priority? (recovery/effectiveness): ").strip()

# Select the best option
best_option = None
best_score = -1

for name, data in surgical_options.items():
    if data["risk"] <= risk_tolerance:
        score = data[priority]
        if score > best_score:
            best_score = score
            best_option = name

# Display result
print("\n--- Result ---")
if best_option:
    print(f"The best surgical option for you is: {best_option}")
else:
    print("No suitable option found within your risk tolerance.")

Sample Output:


Maximum acceptable risk (1 to 5): 3  
What is your priority? (recovery/effectiveness): effectiveness  

--- Result ---  
The best surgical option for you is: robotic_assisted

Explanation:

- Surgical options are defined with attributes: risk, recovery time, and effectiveness
- The user inputs their maximum risk tolerance and treatment priority
- The program filters and scores each option based on the priority
- The highest-scoring option within the risk limit is selected and displayed


Written & researched by Dr. Shahin Siami