💖💖作者：计算机编程小咖 💙💙个人简介：曾长期从事计算机专业培训教学，本人也热爱上课教学，语言擅长Java、微信小程序、Python、Golang、安卓Android等，开发项目包括大数据、深度学习、网站、小程序、安卓、算法。平常会做一些项目定制化开发、代码讲解、答辩教学、文档编写、也懂一些降重方面的技巧。平常喜欢分享一些自己开发中遇到的问题的解决办法，也喜欢交流技术，大家有技术代码这一块的问题可以问我！ 💛💛想说的话：感谢大家的关注与支持！ 💜💜 网站实战项目 安卓/小程序实战项目 大数据实战项目 深度学习实战项目
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智能医疗辅助系统介绍
智能医疗辅助系统是一套基于现代化技术架构开发的综合性医疗管理平台，采用B/S架构设计，支持Java和Python两种开发语言实现，其中Java版本基于Spring Boot框架（整合Spring+SpringMVC+Mybatis），Python版本采用Django框架，前端统一使用Vue+ElementUI+HTML技术栈，数据库采用MySQL进行数据存储和管理。该系统涵盖了医疗机构日常运营的核心业务流程，包括系统首页展示、个人中心管理、医生和患者信息管理、医生排班管理、科室管理等基础功能模块，同时提供预约挂号管理、就诊记录管理、电子病历管理等核心医疗业务功能，并集成预测管理功能以支持医疗数据分析。系统还配备完善的后台管理功能，包括系统管理、公告资讯发布与分类管理、关于我们页面、系统简介展示、轮播图管理等辅助功能模块。整个系统界面设计简洁美观，操作流程符合医疗行业实际使用习惯，能够有效提升医疗机构的信息化管理水平，为医生、患者和管理人员提供便捷的数字化服务体验，是一套功能完整、技术先进、实用性强的智能医疗管理解决方案。
智能医疗辅助系统演示视频
智能医疗辅助系统演示图片
智能医疗辅助系统代码展示
import org.apache.spark.sql.SparkSession;
import org.apache.spark.sql.Dataset;
import org.apache.spark.sql.Row;
import org.springframework.web.bind.annotation.*;
import org.springframework.beans.factory.annotation.Autowired;
import java.time.LocalDateTime;
import java.util.*;
@RestController
@RequestMapping("/medical")
public class MedicalController {
@Autowired
private SparkSession sparkSession = SparkSession.builder().appName("MedicalDataAnalysis").master("local[*]").getOrCreate();
@PostMapping("/appointment/create")
public Map<String, Object> createAppointment(@RequestBody Map<String, Object> appointmentData) {
Map<String, Object> result = new HashMap<>();
String patientId = (String) appointmentData.get("patientId");
String doctorId = (String) appointmentData.get("doctorId");
String appointmentTime = (String) appointmentData.get("appointmentTime");
String departmentId = (String) appointmentData.get("departmentId");
if (patientId == null || doctorId == null || appointmentTime == null) {
result.put("status", "error");
result.put("message", "预约信息不完整");
return result;
}
String conflictQuery = "SELECT COUNT(*) as count FROM appointments WHERE doctor_id = '" + doctorId + "' AND appointment_time = '" + appointmentTime + "' AND status != 'cancelled'";
Dataset<Row> conflictResult = sparkSession.sql(conflictQuery);
long conflictCount = conflictResult.first().getLong("count");
if (conflictCount > 0) {
result.put("status", "error");
result.put("message", "该时段医生已有预约");
return result;
}
String scheduleQuery = "SELECT COUNT(*) as count FROM doctor_schedule WHERE doctor_id = '" + doctorId + "' AND work_date = DATE('" + appointmentTime + "') AND status = 'available'";
Dataset<Row> scheduleResult = sparkSession.sql(scheduleQuery);
long scheduleCount = scheduleResult.first().getLong("count");
if (scheduleCount == 0) {
result.put("status", "error");
result.put("message", "医生该时段不在班");
return result;
}
String appointmentId = UUID.randomUUID().toString();
String insertQuery = "INSERT INTO appointments (id, patient_id, doctor_id, appointment_time, department_id, status, create_time) VALUES ('" + appointmentId + "', '" + patientId + "', '" + doctorId + "', '" + appointmentTime + "', '" + departmentId + "', 'confirmed', '" + LocalDateTime.now() + "')";
sparkSession.sql(insertQuery);
String updateScheduleQuery = "UPDATE doctor_schedule SET appointment_count = appointment_count + 1 WHERE doctor_id = '" + doctorId + "' AND work_date = DATE('" + appointmentTime + "')";
sparkSession.sql(updateScheduleQuery);
result.put("status", "success");
result.put("message", "预约成功");
result.put("appointmentId", appointmentId);
return result;
}
@PostMapping("/medical-record/create")
public Map<String, Object> createMedicalRecord(@RequestBody Map<String, Object> recordData) {
Map<String, Object> result = new HashMap<>();
String patientId = (String) recordData.get("patientId");
String doctorId = (String) recordData.get("doctorId");
String diagnosis = (String) recordData.get("diagnosis");
String symptoms = (String) recordData.get("symptoms");
String treatment = (String) recordData.get("treatment");
String prescription = (String) recordData.get("prescription");
if (patientId == null || doctorId == null || diagnosis == null) {
result.put("status", "error");
result.put("message", "病历信息不完整");
return result;
}
String patientQuery = "SELECT COUNT(*) as count FROM patients WHERE id = '" + patientId + "' AND status = 'active'";
Dataset<Row> patientResult = sparkSession.sql(patientQuery);
long patientCount = patientResult.first().getLong("count");
if (patientCount == 0) {
result.put("status", "error");
result.put("message", "患者信息不存在或已失效");
return result;
}
String doctorQuery = "SELECT COUNT(*) as count FROM doctors WHERE id = '" + doctorId + "' AND status = 'active'";
Dataset<Row> doctorResult = sparkSession.sql(doctorQuery);
long doctorCount = doctorResult.first().getLong("count");
if (doctorCount == 0) {
result.put("status", "error");
result.put("message", "医生信息不存在或已失效");
return result;
}
String recordId = UUID.randomUUID().toString();
String insertRecordQuery = "INSERT INTO medical_records (id, patient_id, doctor_id, diagnosis, symptoms, treatment, prescription, create_time, status) VALUES ('" + recordId + "', '" + patientId + "', '" + doctorId + "', '" + diagnosis + "', '" + symptoms + "', '" + treatment + "', '" + prescription + "', '" + LocalDateTime.now() + "', 'active')";
sparkSession.sql(insertRecordQuery);
String visitRecordQuery = "INSERT INTO visit_records (id, patient_id, doctor_id, visit_time, medical_record_id, status) VALUES ('" + UUID.randomUUID().toString() + "', '" + patientId + "', '" + doctorId + "', '" + LocalDateTime.now() + "', '" + recordId + "', 'completed')";
sparkSession.sql(visitRecordQuery);
String updatePatientQuery = "UPDATE patients SET last_visit_time = '" + LocalDateTime.now() + "', visit_count = visit_count + 1 WHERE id = '" + patientId + "'";
sparkSession.sql(updatePatientQuery);
String historyQuery = "SELECT diagnosis FROM medical_records WHERE patient_id = '" + patientId + "' AND status = 'active' ORDER BY create_time DESC LIMIT 5";
Dataset<Row> historyResult = sparkSession.sql(historyQuery);
List<String> diagnosisHistory = new ArrayList<>();
historyResult.collectAsList().forEach(row -> diagnosisHistory.add(row.getString("diagnosis")));
result.put("status", "success");
result.put("message", "病历创建成功");
result.put("recordId", recordId);
result.put("diagnosisHistory", diagnosisHistory);
return result;
}
@PostMapping("/prediction/analyze")
public Map<String, Object> analyzePrediction(@RequestBody Map<String, Object> analysisData) {
Map<String, Object> result = new HashMap<>();
String analysisType = (String) analysisData.get("analysisType");
String timeRange = (String) analysisData.get("timeRange");
String departmentId = (String) analysisData.get("departmentId");
if (analysisType == null || timeRange == null) {
result.put("status", "error");
result.put("message", "分析参数不完整");
return result;
}
String baseQuery = "SELECT * FROM medical_records WHERE create_time >= DATE_SUB(NOW(), INTERVAL " + timeRange + " DAY)";
if (departmentId != null && !departmentId.isEmpty()) {
baseQuery += " AND department_id = '" + departmentId + "'";
}
Dataset<Row> medicalData = sparkSession.sql(baseQuery);
if (medicalData.count() == 0) {
result.put("status", "error");
result.put("message", "指定时间范围内无数据");
return result;
}
if ("disease_trend".equals(analysisType)) {
String trendQuery = "SELECT diagnosis, COUNT(*) as count FROM (" + baseQuery + ") GROUP BY diagnosis ORDER BY count DESC LIMIT 10";
Dataset<Row> trendResult = sparkSession.sql(trendQuery);
Map<String, Long> diseaseStats = new HashMap<>();
trendResult.collectAsList().forEach(row -> diseaseStats.put(row.getString("diagnosis"), row.getLong("count")));
result.put("diseaseStats", diseaseStats);
} else if ("patient_flow".equals(analysisType)) {
String flowQuery = "SELECT DATE(create_time) as visit_date, COUNT(*) as patient_count FROM (" + baseQuery + ") GROUP BY DATE(create_time) ORDER BY visit_date";
Dataset<Row> flowResult = sparkSession.sql(flowQuery);
Map<String, Long> patientFlow = new HashMap<>();
flowResult.collectAsList().forEach(row -> patientFlow.put(row.getString("visit_date"), row.getLong("patient_count")));
result.put("patientFlow", patientFlow);
long totalPatients = medicalData.count();
long avgDaily = totalPatients / Integer.parseInt(timeRange);
result.put("avgDailyPatients", avgDaily);
}
String doctorWorkloadQuery = "SELECT doctor_id, COUNT(*) as workload FROM (" + baseQuery + ") GROUP BY doctor_id ORDER BY workload DESC LIMIT 5";
Dataset<Row> workloadResult = sparkSession.sql(doctorWorkloadQuery);
Map<String, Long> doctorWorkload = new HashMap<>();
workloadResult.collectAsList().forEach(row -> doctorWorkload.put(row.getString("doctor_id"), row.getLong("workload")));
result.put("doctorWorkload", doctorWorkload);
result.put("status", "success");
result.put("message", "数据分析完成");
result.put("analysisTime", LocalDateTime.now().toString());
return result;
}
}
智能医疗辅助系统文档展示
💖💖作者：计算机编程小咖 💙💙个人简介：曾长期从事计算机专业培训教学，本人也热爱上课教学，语言擅长Java、微信小程序、Python、Golang、安卓Android等，开发项目包括大数据、深度学习、网站、小程序、安卓、算法。平常会做一些项目定制化开发、代码讲解、答辩教学、文档编写、也懂一些降重方面的技巧。平常喜欢分享一些自己开发中遇到的问题的解决办法，也喜欢交流技术，大家有技术代码这一块的问题可以问我！ 💛💛想说的话：感谢大家的关注与支持！ 💜💜 网站实战项目 安卓/小程序实战项目 大数据实战项目 深度学习实战项目
