Two members of EVO-ML, Prof.Hossam Faris and Maria Habib have published their first joint research work with Altibbi in the prestigious Journal of Biomedical Informatics (impact factor: 3.526, Q1). In this work, the data science team at Altibbi developed an intelligent specialty classification model that automatically classifies medical questions of patients into medical specialties and supports the Arabic language in the MENA region.
Altibbi is the first and largest platform in the Arab region that offers telemedicine consultation services such as answering customers’ health and medical questions. A crucial step for answering questions is assigning the questions to the correct class of speciality and, in turn, to a relevant doctor. The motivating reason for automating the text classification process is the fact that Altibbi receives over 4000 health questions per day, which makes the manual classification of questions cumbersome and a waste of time and resources. Furthermore, due to the nature of the speciality itself or sometimes the ambiguity in the language in which the question is asked, classifying the question into one of a large number of specialities is not a trivial task.
The experimental results show that the model has a very promising accuracy of 85%. In addition, the data science team at Altibbi is planning to do further investigation and development in this direction in an attempt to increase the accuracy of the model.
Maria has recently joined Altibbi as a data scientist, while Professor Hossam is directing their data science team which is working on several data science and machine learning based projects for improving the services provided to the patients.
Useful links:
https://www.sciencedirect.com/science/article/abs/pii/S1532046420301532
Great work
Promising research work