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White aper Aug 9, 2020 date-icon

The Impact Of Implementing Telehealth On Pregnancy Related Topics

Pregnancy and childbirth are some of the most important events in a woman's health, starting from conception and to the actual birth event. During pregnancy, women are concerned with so many things, including her fetus development, how she will perceive different pregnancy-related changes, and prepare herself for labor and delivery.Females seek health advice starting from planning the pregnancy, the conception, delivery, and the puerperium which is the 6 weeks duration after delivery. Interaction with the health care system like the telehealth system creates opportunities to address all the concerns a woman might face during her pregnancy by laying a strong base for the ongoing health of the woman and her fetus. Telehealth services have a major impact on women’s healthcare during these phases, by educating and providing the necessary advice to walk through the changes that a woman might experience once planning the pregnancy or the pregnancy itself. Most women in the MENA region find some difficulties in presenting themselves to a general practitioner or obstetrician especially in the early phases of pregnancy. Last year, Altibbi telehealth service contributed to the reduction of doctor’s visits in 17,540 maternity cases, which made up 5.6% of the total consultations held by Altibbi telehealth service.In this paper, we will show Altibbi users’ interest in implementing telehealth services in the maternity-related topics. We will breakdown the consultations based on the country, the age median, and the average age of the users, the preferred way to consult a doctor, and any educational or complications concerns.

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Private Paper Jul 29, 2020 date-icon

Medical Specialty Classification System based on Binary Particle Swarms and Ensemble of One vs. Rest Support Vector Machines

Nowadays, artificial intelligence plays an integral role in medical and healthcare informatics. Developing an automatic question classification and answering system is essential for coping with constant advancements in science and technology. However, efficient online medical services are required to promote offline medical services. This article proposes a system that automatically classifies medical questions of patients into medical specialties and supports the Arabic language in the MENA region. Text classification is not trivial, especially when dealing with a highly morphologically complex language, the dialectical form of which is the dominant form on the Internet. This work utilizes 15,000 medical questions asked by the clients of Altibbi telemedicine company. The questions are classified into 15 medical specialties. As the number of medical questions received daily by the company has increased, a need has arisen for an automatic classification system that can save the medical personnel much time and effort. Therefore, this article presents an efficient medical speciality classification system based on swarm intelligence (SI) and an ensemble of support vector machines (SVMs). Particle swarm optimization (PSO) is an SI-based and stochastic metaheuristic algorithm that is adopted to search for the optimal number of features and tune the hyperparameters of the SVM classifiers, which are deployed as oneversus- rest for multi-class classification. In addition, PSO is integrated with various binarization techniques to boost its performance. The experimental results show that the proposed approach accomplished remarkable performance as it achieved an accuracy of 85% and a features reduction rate of 95.9%.

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White aper Jul 19, 2020 date-icon

The Impact of COVID-19 Pandemic on Mental Health Teleconsultations

This is a whitepaper published by altibbi.com comparing the numbers of mental health consultations during COVID-19 pandemic with the year prior.

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