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Introduction: Bee sting to the cornea is a relatively rare environmental injury that can result in vision loss of different degrees. This study aimed to review the clinical features, pathogenesis, and management of keratopathy caused by corneal bee sting and present a case of keratitis with hypopyon and iridocyclitis secondary to bee sting injury without a retained stinger. Case Presentation: A 47-year-oldman was presented for eyelid edema, severe pain, redness, and impaired vision following a corneal bee sting. On examination, we observed striate keratitis, focal infiltration with diffuse corneal edema, and iridocyclitis under the slit lamp. We also noted trace cells and empyema in the anterior chamber prompted by infection. No retained stinger was detected. A treatment strategy with corticosteroids in combination with broad-spectrum topical antibiotics started and the symptoms resolved significantly. At a three-week follow-up, the cornea restored transparency without complications and visual acuity maintained 20/20. Conclusions: Following bee sting injury, it is crucial to monitor the progression, manifestations, and development of inflammation and infection. Individual timing, symptoms, severity, and complications vary in each case due to various compositions of bee venom. Therefore, assessment and careful follow-up of evolving manifestations may lead to better therapeutic decisions.

Massive hyphaema presentation after a laser iridotomy is very rare. We report a 63-year-old man with ischaemic heart disease on dual antiplatelet therapy (aspirin plus ticagrelor) who was diagnosed as a primary angle-closure suspect and was to undergo a neodymium-doped yttrium aluminium garnet laser iridotomy at Centro Oftalmologico Virgilio Galvis, Floridablanca, Colombia in 2016. While performing the iridotomy in the left eye, active bleeding occurred that finally filled approximately 75 % of the anterior chamber. Intraocular pressure (IOP) increased to 62 mmHg. Mannitol and a topical dorzolamide / timolol were used to control the increase in IOP. The hyphaema slowly resolved over the following week without sequelae. This case revealed that massive hyphaema can complicate laser iridotomy in patients on dual antiplatelet therapy, although this is rare. Therefore, if patients are taking aspirin and ticagrelor, it would be advisable to stop the second medication if possible. In addition, sequential application of photocoagulation and photodisruption lasers might diminish the risk of significant bleeding.

Classification is the task of assigning object to one of several predefined categories. Classification analysis is the organization of data in given classes. Also known as supervised classification, the classification uses given class labels to order the objects in the data collection. Classification approaches normally use a training set to train the model where all objects are already associated with known class labels. The classification algorithm learns from the training set and builds a model to classify the target,. The classification analysis would generate a model that could be used to find a class (target). A neural network consists of patterns represented in terms of numerical values attached to the nodes of the graph and transformations between patterns achieved via simple message-passing algorithms. Certain of the nodes in the graph are generally distinguished as being input nodes or output nodes, and the graph as a whole can be viewed as a representation of a multivariate function linking inputs to outputs. Numerical values (weights) are attached to the links of the graph, parameterizing the input/output function and allowing it to be adjusted via a learning algorithm. Artificial neural networks (ANNs) consider the good tool to learn and classify patterns such as the biological human brain learning process. It consists of simple elements called neurons, which are operating in parallel (included many neuron units that work in parallel). Connections between neurons have weights emerged with the inputs of the neural to give the certain output. The connection's weights have been adjusted during the learning process by iteratively comparing the output of the network and the required target. The ability of the network to show a good performance in the results depends on the training algorithm. There are different types of neural networks, however, most of researches published in the medical studies used one class of neural networks, the back-propagation (BP).