In Senegal, there is 1 ophthalmologist per 507,000 inhabitants whereas the World Health Organization (WHO) standard is 1 ophthalmologist per 250,000 inhabitants. In addition, out of the country's 14 regions, 6 regions have no ophthalmologist. 84% of ophthalmologists are stationed in the capital, Dakar. Rural areas lack qualified human resources. WHO estimates that 88.4 million people worldwide are visually impaired as a result of uncorrected refractive errors such as amblyopia (irreversible visual impairment). It is a cause of children dropping from school. One of the causes of amblyopia is strabismus. Strabismus is a defect in the parallelism of the eyes. WHO estimates the worldwide prevalence rate of strabismus at 2 to 5% in Caucasians and 0.37 to 1.5% in African melanoderma. It is important to diagnose children at an early age so that they can be treated quickly. The objective is to spare them a visual handicap in the future. To assist ophthalmologists, automatic diagnostic methods for strabismus based on artificial intelligence approaches have been proposed in the literature. In this article, we provide an overview of projects that involve the use of image processing basic techniques, machine learning and deep learning approaches for strabismus diagnosis and angular deviation calculation.