This is an open-tabled, one-arm observatory trial to assess the effectiveness and safetyof the Autonomous Treatment System Based on Machine Learning in patients with Covid-19,Post-Acute Sequelae of SARS-CoV-2 infection and influenza.
This study has enrolled 27 patients diagnosed with Covid-19, Post-Acute Sequelae of
SARS-CoV-2 infection, and influenza. Of these patients, 26 are outpatients, and 1 is
hospitalized. After screening based on the inclusion and exclusion criteria, eligible
patients will receive prescriptions recommended by the Autonomous Treatment System Based
on Machine Learning in this observational trial.
The objectives of this study are:
1. To compare the classifications made by our machine learning system with those by
physicians to assess the model's reliability and accuracy;
2. To evaluate Covid-19-related hospitalizations or deaths from any cause through day
28;
3. To determine if the machine learning system's recommended prescription alleviates
symptoms of Covid-19, Post-Acute Sequelae of SARS-CoV-2 infection, and influenza;
4. To monitor participants who tested positive for the Covid-19 for 28 days after
initiating treatment, looking for potential rebound cases.
Participants will use an online application to receive the recommended prescription
results and will forward these results to a physician for verification. Patients are
instructed to complete the online analysis every 3 days or whenever their symptoms
change, whichever comes first. They are also asked to adhere to the prescribed medication
regimen. Research physicians will conduct follow-ups with patients every 3 days via phone
calls. The potential treatments patients may receive include any of the following
Traditional Chinese Medicine formulas: LizCovidCure-1, LizCovidCure-2, LizCovidCure-3,
LizCovidCure-4, and LizCovid-5.
Other: Autonomous Treatment System for Covid-19, Post-Acute Sequelae of SARS-CoV-2 Infection and Influenza Based on Machine Learning
A novel treatment recommendation system for Covid-19, Post-Acute Sequelae of SARS-CoV-2
Infection and Influenza, which is based on machine learning
Inclusion Criteria:
- Either male or female (14 years or older), and their COVID-19 vaccination status was
not a factor for inclusion.
- Subjects with any high-risk conditions
- Subjects with positive sars-cov-2 rapid antigen results in 30 days
- Subjects with post Covid-19 syndrome
Exclusion Criteria:
- pregnant individuals
- subjects with known histories of allergic reactions to medical herbs commonly used
in Traditional Chinese Medicine (TCMs)
Sheng'Ai Traditional Medicine Hospital
Kunming 1804651, Yunnan 1785694, China
jiale xian, MHA, Study Chair
Lizora LLC