In the US alone, there are over 1 Million injuries that happen annually as a result of Prescription Errors. AI has the ability to Identify and prevent medication related errors, possibly via outlier analysis and anomaly detection. Flag medications that conflict with the profile of the patient, physician, or institution
Understand the Use-case under 5 minutes
Article (3 minutes)
Learn how Artificial intelligence can bolster doctors’ decision making and eliminate errors using machine learning and pattern recognition algorithms
Read
Using Computer Vision AI to Detect Medication Errors in Hospitals
Read
Article (2 minutes)
Learn how AI could help save thousands of Americans who die each year because of preventable medication errors, and it’s potential role in controlling the opioid epidemic.
Read
Get to know more Business and Technical details about the use-case (15-30 minutes)
More detailed introduction covering business and technical aspects
Video (15 minutes)
Reducing Drug Prescription Errors and Adverse Drug Events with a Machine Learning-Based Clinical Decision Support System
Watch
Article (3 minutes)
A hybrid AI decision-support system trained on data from more than 10,000 patients, and how it makes predictions at the patient level rather than focusing on individual prescription orders.
VisitCase studies, Organizational Aspects, Return on Investment examples
Case Study
Researchers find a savings of more than one million dollars and prevention of hundreds, if not thousands, of adverse drug events could have been had with machine learning system
Read
MedEye, a medication safety system powered by AI to help nurses stop and prevent medication errors, has prevented 100,000 medication errors including ~13,000 related to incorrect dose
ReadMore details on the technical aspects of the use-case
Blog (6 minutes)
See how, based on the patient’s current clinical state and medical history, a machine learning model was able to anticipate physician’s actual prescribing decisions three quarters of the time
Visit
Paper
A clinical decision support system that used a probabilistic, ML approach based on statistically derived outliers to detect medication errors generated clinically useful alerts
Read
Technical resources that will help you implement the use-case (notebooks, tutorials..)
Github Repo
In the experiments, this approach achieves better results in the task of overdose and underdose detection in medical prescriptions, compared to other methods applied to this problem
Visit
This study conducted by Google examines the ability of machine-learning models to provide patient & time-specific predictions of medication orders based on information in electronic health records
Visit
Paper
A hybrid AI decision support system—combining machine learning and a rule-based expert system—in a typical hospital setting. This system is making prediction at the patient level
Read
Data Sets you can use to build Demos, POCs, or test Algorithms
Please keep an eye on this page, we'll have some relevant data sets you very soon!
Got a Question or a Resource to share with the Community? Please do!
Copyright © 2024 AI Cases. All rights reserved
Session expired
Please log in again. The login page will open in a new tab. After logging in you can close it and return to this page.
Where is the dataset?
Hi Amany, we couldn’t find a good dataset for this use-case yet. We’ll make sure to let you know once we do!