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Artificial Intelligence in Children's Clinic

2019-12-10 01:20:59 | BioPortfolio

Summary

At the third-class hospital in China, outpatients are in the majority and doctors have a heavy workload. Therefore, the phenomenon of long waiting time and short treatment time seems to be common. As a result, patients may not clearly recall and describe all their illnesses in such a limited time. Meanwhile, the high workload increases the burden of doctors and reduces the satisfaction of patients. The application of auxiliary diagnosis in the outpatient process allows patients enough time to review the development of their conditions, and describe their conditions in detail. It greatly reduces the time spent waiting in line and reduced the burden on doctors. The investigator's project aims to create a human-computer integrated diagnosis and treatment system, just like doctor assistants, to develop a new diagnosis and treatment process embedded with Artificial Intelligence (AI). This study is helpful to optimize the diagnosis process, improve the quality of medical treatment and promote the construction of medical alliance. Therefore, in line with the requirements of hierarchical diagnosis and treatment in China, it is conducive to the rational distribution of medical resources and of great significance to medical and health reform.

Description

Relying on mobile application and computer software, it would achieve:

1. Intelligent guidance before treatment, and matching the department;

2. Intelligent medical history collection, and AI medical record generation;

3. Automatically recommend examination items;

4. Assist in clinical diagnosis and make intelligent diagnosis suggestion.

Study Design

Conditions

Artificial Intelligence

Intervention

Routine diagnostic process, Artificial intelligence assisted diagnosis process

Location

Shanghai Children's Medical Center, Shanghai Jiao Tong University School of Medicine
Shanghai
Shanghai
China
200127

Status

Not yet recruiting

Source

Shanghai Jiao Tong University School of Medicine

Results (where available)

View Results

Links

Published on BioPortfolio: 2019-12-10T01:20:59-0500

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