Difference between revisions of "Healthcare AI Use Cases"
From PatientRecovery
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==ClosedLoop AI Use Cases== | ==ClosedLoop AI Use Cases== | ||
Hospitals <br> | Hospitals <br> | ||
| − | * [https://news.mit.edu/2020/closedloop-ai-predictive-health-care-0619?utm_source=miragenews&utm_medium=miragenews&utm_campaign=news ''Appointmnet No-Shows | + | * [https://news.mit.edu/2020/closedloop-ai-predictive-health-care-0619?utm_source=miragenews&utm_medium=miragenews&utm_campaign=news '''Appointmnet No-Shows''' - Predict patients most likely to miss appointments] |
* [https://news.mit.edu/2020/closedloop-ai-predictive-health-care-0619?utm_source=miragenews&utm_medium=miragenews&utm_campaign=news Predict patients most likely to acquire infections like sepsis] | * [https://news.mit.edu/2020/closedloop-ai-predictive-health-care-0619?utm_source=miragenews&utm_medium=miragenews&utm_campaign=news Predict patients most likely to acquire infections like sepsis] | ||
* [https://news.mit.edu/2020/closedloop-ai-predictive-health-care-0619?utm_source=miragenews&utm_medium=miragenews&utm_campaign=news Predict patients most likely to benefit from periodic check ups] | * [https://news.mit.edu/2020/closedloop-ai-predictive-health-care-0619?utm_source=miragenews&utm_medium=miragenews&utm_campaign=news Predict patients most likely to benefit from periodic check ups] | ||
Revision as of 07:45, 10 July 2020
ClosedLoop AI Use Cases
Hospitals
- Appointmnet No-Shows - Predict patients most likely to miss appointments
- Predict patients most likely to acquire infections like sepsis
- Predict patients most likely to benefit from periodic check ups
- Out of Network Leakage
Health Insurers
- Risk Adjustment
- Predict patient readmissions and the onset or progression of chronic diseases.
- Predict patient onset or progression of chronic diseases.
- Identify patients' with collapsed lungs - artificial intelligence-enabled mobile X-ray system flags images of patients who need immediate intercession, ensuring that patients with collapsed lungs receive more timely care. (7/8/20)
- Predicts patients' hospitalization risk and triages them to appropriate care - uses AI tech, EHR data and a questionnaire to perform clinical intake of patients visiting ER, Urgent Care or Home (6/30/20)
- Diagnosed breast cancer at a higher rate than 11 pathologists. AI model using algorithms and deep learning (12/12/17)
