Health and Wellness
Medical Certificate (MC) Named Entity Recognition Model
An Artificial Intelligence (AI) model was developed to extract essential information from scanned medical certificates. Trained to identify Medical Certificate (MC) that are issued in Singapore, the model enables prompt and precise auto-approval of medical leave requests.
Technology overview
The presented technology is an Artificial Intelligence (AI) model developed to extract essential information from scanned medical certificates. This trained model can extract pertinent details from medical certificates issued locally in Singapore, aiding companies in streamlining their medical leave management process by automating the approval of medical leave requests.
The extracted details can seamlessly integrate with a company’s existing workflow. The technology enables prompt and precise handling of leave requests, thereby reducing administrative workload, processing time, and errors introduced due to manual entry.
Technology features
The trained AI model recognises terms and entities from scanned medical certificates. This includes, but is not limited to:
Clinic Name
Clinic Address
Clinic Telephone Number
Patient Name
Start & End Date of Medical Leave
Duration of Medical Leave
The Name Entity Recogniser (NER) model is trained based on an open-source library and can be seamlessly integrated with the existing workflow or system to automate the extraction of information for approval or recording purposes.
Potential applications
The model, in its current state, has been trained on a diverse dataset of medical certificates issued in Singapore and is suitable for application in systems providing Document Management and Human Resource solutions. The model’s application will be particularly useful for:
Companies seeking to automate their medical leave processing or application workflow.
Insurance providers and vendors specialising in Document Management, HR software solutions, Payroll, and Attendance solutions.
The model can be integrated into an existing solution to add value in the processing of medical certificates.
Benefits
The model is implemented using Natural Language Processing and operates in the domain of Named Entity Recognition. It has been trained using a diverse dataset of medical certificates issued in Singapore and can automatically recognise entries of interest from a scanned copy of the document. The model accommodates variations of formats, prints, and naming of the entries and provides a recognisable input to the software systems that utilise it.
Commercialisation
This technology is available for licensing and technology transfer.
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