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The Perfect Problem Based Learning for Medical students in form of interactive AI simulated patients.

The inventor and doctors at meksi have identified that the current methods of assessing medical student competencies through case study role plays is entirely manual. It is time consuming, expensive and is not standardised.

In education and training, a person’s learning is often subject to a series of assessments to the competency of the person. For example, during a learning exercise a person may be presented with a series of questions and the person writes an appropriate set of answers. This is then marked or scored by a tutor or examiner. In training professionals, such as a Doctor, lawyer or engineer, the person’s training may be provided with a problem that needs to be addressed. A medical student or Doctor may be presented with a patient with one or more symptoms. That person then needs to make an assessment and diagnosis of the patient by exploring their medical history, undertaking a physical examination, ordering relevant investigations and finally making an assessment.

By automating/computerising the process of assessment and channeling doctors learning, it would lead to standardisation of medical education rapidly and that to on a global scale.

This would bring about an improvement in human lives by bridging the standards between the classroom and remote community physicians.

2016 - Australian Innovation Patent

2017 - MVP Ready

2017 - HCF Catalyst Finalist

2018 - Artesian Capital Investment

2018 - ESIC Eligible

2018 - Participant HCF Catalyst Program powered by Slingshot

2018 - Proof of concept trial- Medi Sys subsidiary company of NEA

2018 - HCF Catalyst Demo Day

2018 - Incorporate IBM Watson Technology