Anales de la RANM

267 A N A L E S R A N M R E V I S T A F U N D A D A E N 1 8 7 9 DEEP LEARNING GENITAL LESIONS IMAGE CLASSIFICATION González-Alday R, et al. An RANM. 2022;139(03): 266 - 273 The burden of these diseases is most notable in low and middle-income countries. However, the health, social and economic problems caused by the high prevalence of STDs are a significant concern all around the world (2,3), and even more in the last few years, with higher rates of transmission, emerging outbreaks and antimicrobial resistances increasing (4). Diagnosis of these diseases is usually done through a physical examination —either by a general practi- tioner or a specialist—, with further tests if needed and available. While in many cases STDs might be asymptomatic, common symptoms include abnormal discharge, lower abdominal pain and genital skin lesions such as ulcers, warts or lumps. A correct and early diagnosis is vital for the proper treatment and information of the patient, and therefore to avoid transmission (3). However, it can be not so obvious for a non-specialist health profes- sional such as a general practitioner or a nurse, or even more complicated in cases when access to healthcare is difficult or when the patient is reluctant to seek medical attention due to social stigma —e.g., social, economic, or religious. In this article we present a prototype of an Artificial Intelligence (AI)-based approach: a deep learning model to automatically classify images of different genital manifestations of STDs. This kind of tool and digital environment could be used to build systems to support medical diagnosis in these develo- ping countries, aiming to create new ways to help non-specialist health providers as well as, in the near or mid future, the patients themselves by providing them with an accurate, easy-to-use medical decision support system. In this study, we decided to choose two kinds of typical STD lesions that will be classified in: typical genital herpes ulcerative lesions as well as genital warts and condylomas, which are usually caused by human papillomaviruses (HPV). These are very common problems within the area of STDs. 1.2. Genital herpes Genital herpes is a very common STD caused by either the herpes simplex virus type 1 (HSV-1) or type 2 (HSV-2). HSV infections are spread through contact with herpes lesions, mucosal surfaces, genital or oral secretions from an infected individual. Most infections are asymptomatic or have very mild symptoms that go unnoticed or that can be easily confused as another skin condition (5). For that reason, even though the highest risk of transmission of HSV happens in periods when visible lesions are present, it is common to become infected by contact with an asymptomatic partner without visible manifestations who might not be aware of their infection. In the case that symptoms do manifest, herpes lesions usually consist of one or more vesicles or small blisters that appear on the genital, rectum or mouth area. These vesicles break and leave painful ulcers that can take two to four weeks to heal after the initial infection, and can be accompanied by other symptoms like fever, body aches, swollen lymph nodes, or headache. Recurrent episodes of genital herpes are common, especially for HSV-2 infections, and are usually preceded by prodromal symptoms such as localized pain or tingling. However, recurrent herpes outbreaks tend to be milder than the first one, which is often associated with a longer duration of herpetic lesions and systemic symptoms, as well as increased viral shedding that increases the risk of transmission (6). 1.3. Human papillomavirus Human papilloma virus (HPV) is one of the most frequently sexually transmitted viruses. In fact HPV is so widespread that, if unvaccinated, almost every sexually active person will get HPV at some point in their lifetime (7). This virus is usually transmitted by direct skin-to- skin or mucosal contact, commonly via vaginal, oral or anal sex. The virus is usually cleared out in a period of about two years without causing health issues, however, in other cases HPV can cause signifi- cant problems. These include genital warts, which are small bumps in the anogenital area, or condylomas, which are more raised, cauliflower-like growths, as well as other complications such as cervical, penile, anal and oropharyngeal cancer. There are HPV tests that can screen for cervical cancer, used for women above 30 years of age, however, there is currently no approved test for HPV in men, nor is it recommended for younger women, so in order to diagnose it, a physical examination to identify HPV lesions should be carried out, with an additional biopsy in if the diagnosis is uncertain or if cancer is suspected. 1.4. Deep learning in medicine While AI has been applied to medicine since the 1970s, the recent emphasis on data-driven techni- ques in the area of machine learning have shown the substantial AI possibilities in a wide variety of fields, with countless applications. Its capacity to facilitate —and even automate— many types of tasks, with a performance sometimes surpas- sing human performance, has transformed many areas of medicine. If AI was focused in the period from 1970 to 1990 in knowledge-based systems — with the clear example of expert systems—, since the 1990s the predominance of AI in medicine has been transferred to data-based systems. The recent explosion of medical data available from many sources has fueled such a predominance. In this context, a technique called deep learning (8) — whose roots can be traced back to the 1940s, with