Patient Screening and Recruitment
In the process of drug research and development, the indirect cost caused by the extension of time
cannot be ignored. In practice, most clinical trials have to significantly extend their schedule, because it is
difficult to find enough patients in the original time. AI relies on deep learning ability, which can extract
relevant information from massive clinical trial data. MedAI’s AI system can automatically match the trial
results with the patient's situation, improve the efficiency of accurate matching, and complete the trial
recruitment in a short time.
Big data report of clinical recruitment in real-time.
Offline recruitment of appropriate patients for clinical trials.
Screen patient populations dynamically, automatically and intelligently.
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In addition to large-scale
medical information and
clinical trial database,
wearable devices and machine
learning can be applied to
improve patient participation,
data quality and operation
efficiency in clinical trials.
Complete data extraction
obtained in the clinical trial
files using deep learning
techniques, and realize the
rapid recruitment of patients.
Upload results into medical
records of subjects and clinical
trial databases to achieve real-
time accurate matching and
Artificial Intelligence in Patient Screening and
The clinical trial managers need to find out patients who meet the drug test from a large number of cases,
and inform the subjects that they should participate in the relevant tests in time. In clinical trials,
improving patient interaction and ultimately obtaining numerous practical data are essential for drug
development breakthroughs. By using the in-depth research of disease data with artificial intelligence,
pharmaceutical enterprises can more accurately mine target patients and quickly achieve patient