医生推荐系统，一键轻松找名医，健康难题轻松搞定

2023-04-24 14:08:33

医生推荐系统：您的医疗保健指南

疾病自诊：了解您的症状

疾病自诊是一种便捷高效的工具，可帮助您识别潜在的健康问题。只需输入您的症状，医生推荐系统就会使用庞大的医学知识库进行智能分析，为您提供可能的疾病诊断。这可以帮助您在不进行昂贵和耗时的测试的情况下了解您的健康状况。

代码示例：

import pandas as pd

# 加载症状数据
symptoms = pd.read_csv('symptoms.csv')

# 创建症状到疾病的映射
symptom_to_disease = {}
for index, row in symptoms.iterrows():
    symptom_to_disease[row['symptom']] = row['disease']

# 获取用户的症状
user_symptoms = ['头痛', '发烧', '咳嗽']

# 使用映射确定可能的疾病
possible_diseases = []
for symptom in user_symptoms:
    if symptom in symptom_to_disease:
        possible_diseases.append(symptom_to_disease[symptom])

# 显示可能的疾病
print("可能的疾病：")
for disease in possible_diseases:
    print(disease)

医生推荐：找到最适合您的医生

有了疾病诊断后，下一步就是找到合适的医生。医生推荐系统根据您的疾病情况、就医意愿和其他因素，为您匹配最合适的医生。您可以查看医生的专业、资历、评价和服务指标，以便做出明智的选择。

代码示例：

import numpy as np

# 创建一个医生数据库
doctors = [
    {'id': 1, 'name': 'Dr. Smith', 'specialty': '心血管病', 'years_of_experience': 10},
    {'id': 2, 'name': 'Dr. Jones', 'specialty': '内科', 'years_of_experience': 5},
    {'id': 3, 'name': 'Dr. Brown', 'specialty': '儿科', 'years_of_experience': 15},
]

# 根据用户的疾病和偏好推荐医生
def recommend_doctors(disease, preferences):
    recommended_doctors = []
    for doctor in doctors:
        if doctor['specialty'] == disease:
            recommended_doctors.append(doctor)

    # 根据偏好对医生进行排序
    if preferences['years_of_experience'] == 'more':
        recommended_doctors = sorted(recommended_doctors, key=lambda x: x['years_of_experience'], reverse=True)
    else:
        recommended_doctors = sorted(recommended_doctors, key=lambda x: x['years_of_experience'])

    return recommended_doctors

# 用户的疾病和偏好
disease = '心血管病'
preferences = {'years_of_experience': 'more'}

# 推荐医生
recommended_doctors = recommend_doctors(disease, preferences)

# 显示推荐的医生
print("推荐的医生：")
for doctor in recommended_doctors:
    print(doctor['name'])

医生评价：了解真实口碑

医生评价是了解医生真实口碑的重要工具。医生推荐系统收集患者对医生的评价，并将其公开展示。您可以查看患者的评价内容，了解医生的医术、态度、服务等方面的表现。这可以帮助您在选择医生时做出明智的决定。

医生服务指标评价体系：评估医生表现

医生服务指标评价体系提供了一个客观的标准来评估医生的表现。该系统根据医生的专业水平、服务态度、患者满意度等指标进行综合评价。您可以根据评价结果，选择最适合您的医生。这有助于确保您获得高质量的医疗服务。

代码示例：

import math

# 创建一个医生评价数据库
reviews = [
    {'doctor_id': 1, 'rating': 5, 'comment': '一位优秀的医生'},
    {'doctor_id': 1, 'rating': 4, 'comment': '耐心细致'},
    {'doctor_id': 2, 'rating': 3, 'comment': '态度一般'},
    {'doctor_id': 2, 'rating': 2, 'comment': '服务较差'},
]

# 计算医生的平均评分
def calculate_average_rating(doctor_id):
    total_rating = 0
    num_ratings = 0
    for review in reviews:
        if review['doctor_id'] == doctor_id:
            total_rating += review['rating']
            num_ratings += 1

    if num_ratings > 0:
        return total_rating / num_ratings
    else:
        return 0

# 计算医生的服务指标
def calculate_service_indicators(doctor_id):
    service_indicators = {}

    # 计算患者满意度
    patient_satisfaction = 0
    for review in reviews:
        if review['doctor_id'] == doctor_id:
            patient_satisfaction += review['rating']

    service_indicators['patient_satisfaction'] = patient_satisfaction / num_ratings

    # 计算专业水平
    professionalism = 0
    for review in reviews:
        if review['doctor_id'] == doctor_id and review['rating'] >= 4:
            professionalism += 1

    service_indicators['professionalism'] = professionalism / num_ratings

    return service_indicators

# 用户选择的医生
doctor_id = 1

# 计算医生的平均评分和服务指标
average_rating = calculate_average_rating(doctor_id)
service_indicators = calculate_service_indicators(doctor_id)

# 显示结果
print("医生的平均评分：", average_rating)
print("医生的服务指标：")
for indicator, value in service_indicators.items():
    print(f"{indicator}: {value}")