AI Assisted Doctors to Improve the Accuracy of Abdominal Pain Diagnosis
Study Details
Study Description
Brief Summary
In this study,The investigators present a prospective study of artificial intelligence system to improve the accuracy of abdominal pain diagnosis in physicians. Subjects will be divided into two groups. For the collected medical records, the experimental group will complete the disease diagnosis with the assistance of the artificial intelligence system. Ai-assisted systems can alert doctors in real time which tests need to be perfected and which diagnoses are most likely. Doctors in the control group diagnosed the disease completely according to clinical procedures. Then, compare the accuracy of disease diagnosis with or without the assistance of artificial intelligence, and the cost of diagnosis.
| Condition or Disease | Intervention/Treatment | Phase |
|---|---|---|
|
N/A |
Detailed Description
In recent years, with the continuous development of science and technology, the range of diagnostic tests and biomarkers for disease and treatment modalities has increased exponentially, and medical information has become increasingly complex. This requires the clinician to comprehensively evaluate the patient's condition, so as to choose the best examination and treatment. However, for the complex symptoms in the actual clinical environment, the corresponding diseases are numerous; In the face of complex and heavy clinical work, how to extract the important characteristics of patients' diseases faster and more accurately to achieve high-quality and accurate diagnosis and treatment is the key problem to be solved at present. For example, in the field of digestion, the chief complaint of abdominal pain is one of the most common clinical symptoms of patients seeking medical treatment, and some acute abdominal pain, such as gastrointestinal ulcer perforation, strangulated intestinal obstruction, acute obstructive suppurative cholangitis and other urgent onset, narrow treatment time window, high mortality. Clinicians must make a quick diagnosis and distinguish between those that require emergency intervention and those that do not in order to manage patients in a timely manner and avoid catastrophic events. However, the causes of abdominal pain are many and the mechanisms are complex. In addition, since pain is a subjective sensation and is greatly influenced by subjective factors, there are no clear objective indicators to determine whether or not and the degree of pain, and it is extremely challenging to correctly diagnose and interpret abdominal pain. To this end, the clinician must take a detailed history and perform a thorough physical examination when evaluating a patient's abdominal pain. In recent years, artificial intelligence technology has developed rapidly, especially in the field of medicine has been widely applied research, mainly reflected in the diagnosis and differential diagnosis of diseases, prognosis judgment and clinical decision analysis. Some studies have shown that in terms of auxiliary pathology and imaging diagnosis, AI has reached or even exceeded the average diagnostic level of corresponding specialists. Most of these studies focus on pattern recognition based on images, and the logical judgment based on natural language using medical records information is still in the preliminary development stage. There are no relevant reports on integrating comprehensive information of large medical records to make intelligent prediction of digestive tract diseases.
Study Design
Arms and Interventions
| Arm | Intervention/Treatment |
|---|---|
| Experimental: Experimental: with Artificial intelligence assistant system The doctor completes the disease diagnosis of abdominal pain with the assistance of AI |
Device: Artificial intelligence assistant system
The AI-assisted diagnosis system can provide the direction of disease diagnosis in real time and assist the doctor to give the final diagnosis
|
| No Intervention: No Intervention: without Artificial intelligence assistant system The doctor completes the disease diagnosis of abdominal pain in the routine diagnosis and treatment |
Outcome Measures
Primary Outcome Measures
- Accuracy of diagnosis [one week]
Number of correctly diagnosed diseases/all medical records
Secondary Outcome Measures
- Total diagnostic accuracy [one week]
Number of cases diagnosed correctly by all doctors/Number of cases diagnosed by all doctors * Doctor
- Determine the cost required for diagnosis [one week]
The cost it takes a doctor to make a definitive diagnosis
- Determine the time required for diagnosis [one week]
The time it takes a doctor to make a definitive diagnosis
Eligibility Criteria
Criteria
Inclusion Criteria:
-
The patient visited the hospital because of acute abdominal pain;
-
No definite diagnosis has been made before, and the patient needs to be hospitalized for further diagnosis;
-
Able to read, understand and sign the informed consent form;
-
The investigator believes that the subject can understand the process of the clinical study, and is willing and able to complete all the study procedures, follow- up visits, and cooperate with the study procedures;
Exclusion Criteria:
-
Has participated in other clinical trials, signed the informed consent form and is in the follow-up period of other clinical trials;
-
Drug or alcohol abuse or psychological disorders in the last 5 years;
-
Pregnant or lactating women;
-
High-risk diseases or other special conditions that the investigator considers inappropriate for the subject to participate in the clinical trial.
Contacts and Locations
Locations
| Site | City | State | Country | Postal Code | |
|---|---|---|---|---|---|
| 1 | Renmin Hospital of Wuhan University | Wuhan | Hubei | China | 430060 |
Sponsors and Collaborators
- Renmin Hospital of Wuhan University
Investigators
- Principal Investigator: Honggang Yu, MD, Renmin Hospital of Wuhan University
Study Documents (Full-Text)
None provided.More Information
Publications
None provided.- EA-22-007