Real-world Clinical Study and Medical Machine Intelligence Study for Traditional Chinese Internal Medicine

Real-world Clinical Study and Medical Machine Intelligence Study for Traditional Chinese Internal Medicine by Using Medical Big Data and Artificial Intelligence Methods

This real-world study aimed at 1. exploring the relationships of traditional Chinese medicine (TCM) syndrome and internal diseases, 2. investigating the relationships of TCM treatment and internal diseases, and 3. creating medical machine intelligence to help internal physician in clinical practice. Big data methods and artificial intelligence algorithms are used to assess the associations based on electronic case files of patients.

Study Overview

• Status: Recruiting
• Conditions: Internal Disorders
• Intervention / Treatment: Other: regular medical treatment

• Study Type: Observational
• Enrollment (Anticipated): 2000000

Contacts and Locations

Study Locations

• China
  • Shanghai
    • Shanghai, Shanghai, China, 200040
      • Recruiting
      • Huasha Hospital
      • Contact: Zihui Tang, M.D and Ph.D; Phone Number: +8615821993541; Email: dr_zhtang@yeah.net

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 20 years to 100 years (Adult, Older Adult)
• Accepts Healthy Volunteers: No
• Genders Eligible for Study: All

• Sampling Method: Probability Sample

Study Population

all patients of internal medicine in hospital to include hospital of Chinese medicine and morden hospital in China

Description

Inclusion Criteria:

• all patient records of internal medicine in hospital

Exclusion Criteria:

• subjects with major missing data

Study Plan

How is the study designed?

Design Details

• Observational Models: Case-Only
• Time Perspectives: Other

Number of groups / cohorts

1

Cohorts and Interventions

Group / Cohort	Intervention / Treatment
Group	Other: regular medical treatment; regular medical treatment

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
internal diseases	all of internal diseases	10 years

Collaborators and Investigators

• Sponsor: Shanghai Tongji Hospital, Tongji University School of Medicine
• Collaborators: Huashan Hospital; Puer Hospital of Chinese Medicine; Dangyang Hospital of Chinese Medicine; Changde Hospital affiliated to Hunan University of Chinese Medicine; Ruikang Hospital affiliated to Guanxi University of Chinese Medicine; Shandong Jining No.1 People's Hospital; People's Hospital of Dangyang

Publications and helpful links

General Publications

• Liu J, Xu F, Mohammadtursun N, Lv Y, Tang Z, Dong J. The Analysis of Constitutions of Traditional Chinese Medicine in Relation to Cerebral Infarction in a Chinese Sample. J Altern Complement Med. 2018 May;24(5):458-462. doi: 10.1089/acm.2017.0027. Epub 2017 Aug 18.
• Li X, Lei T, Tang Z, Dong J. Analyzing the association between fish consumption and osteoporosis in a sample of Chinese men. J Health Popul Nutr. 2017 Apr 19;36(1):13. doi: 10.1186/s41043-017-0088-y.
• Geng W, Qin X, Yang T, Cong Z, Wang Z, Kong Q, Tang Z, Jiang L. Model-Based Reasoning of Clinical Diagnosis in Integrative Medicine: Real-World Methodological Study of Electronic Medical Records and Natural Language Processing Methods. JMIR Med Inform. 2020 Dec 21;8(12):e23082. doi: 10.2196/23082.

Study record dates

Study Major Dates

• Study Start (Actual): April 1, 2017
• Primary Completion (Actual): December 30, 2020
• Study Completion (Anticipated): December 30, 2022

Study Registration Dates

• First Submitted: September 5, 2017
• First Submitted That Met QC Criteria: September 5, 2017
• First Posted (Actual): September 7, 2017

Study Record Updates

• Last Update Posted (Actual): January 6, 2021
• Last Update Submitted That Met QC Criteria: January 5, 2021
• Last Verified: January 1, 2021

More Information

Terms related to this study

• Other Study ID Numbers: 20170906

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: No

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No