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. Protheragen’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.
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 dynamic update.
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 recruitment.
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