# Application of Artificial Intelligence in Support of NAFLD Diagnosis
## 1 Introduction  
According to a study conducted back in 2013 [1], non-alcoholic fatty liver disease was already globally prevalent, involving nearly 20% of the world's population. It is a civilization disease that, despite its non-serious symptoms and lack of immediate life-threatening risks, can lead to many dangerous liver diseases. A lack of global awareness and problems with the diagnosis of this disease leads to asymptomatic deterioration of the liver and further progression of the disease. On the other hand, early diagnosis allows the disease to be counteracted relatively quickly, such as through lifestyle and dietary changes. In this work, the authors postulate using an artificial intelligence system to help diagnose this disease automatically. With the lipid profile data that can be acquired during a blood count, such a system can tell a doctor with a very high degree of accuracy the likelihood that a patient is suffering from non-alcoholic fatty liver disease. With the current computing power of computers, such a system can diagnose more patients in seconds than a real doctor can in a day. Of course, such a system will never replace a doctor who needs to make a definitive diagnosis. However, its use will help speed up and increase the quality of diagnostic processes in the hospital [2]. The system is equipped with data pipelines that allow for the aggregation of more data from the hospital and its use to train artificial intelligence models. As described in [3], unfortunately, the decisions made by some artificial intelligence models are currently incomprehensible to the general public, and the models being black boxes cause mistrust. To address this problem, the authors used methods of explained artificial intelligence to create a set of reports and analyses that explain the models' decision-making process in a way that is understandable to the doctor and describes why the system made such a decision and not another. This is a responsible approach to building publicconfidence in such systems. In addition, such analyses allowed the authors to find lipid profile parameters and their values responsible for the disease described above. These conclusions allowed us to determine markers to help doctors in clinical research on this disease and support future diagnoses. Non-alcoholic fatty liver disease is a condition characterized by the accumulation of excess fat in liver cells in people who do not drink large amounts of alcohol. The symptoms of NAFLD can be mild or absent, making it sometimes difficult to diagnose early on. Some of the most common symptoms include fatigue, weight loss, pain in the upper right abdomen, and liver enlargement. Diagnosis of NAFLD usually begins with a medical interview and physical examination. The doctor may order blood tests to assess liver function and the presence of possible inflammatory markers. A critical diagnostic tool is liver ultrasound, which can detect the presence of steatosis. In more advanced cases, a liver biopsy may be necessary [4]. Treatment of NAFLD focuses mainly on lifestyle changes. Weight loss through a healthy diet and regular physical activity is recommended for the mild form of the disease. Avoiding excess saturated and simple fats in the diet and limiting sugar and alcohol intake can also help improve liver health. In cases of advanced NAFLD, the doctor may prescribe medications to control blood sugar, cholesterol, and blood pressure [5]. If NAFLD is not treated, it can lead to severe complications such as cirrhosis, hepatocellular carcinoma, and an increased risk of cardiovascular disease. Therefore, starting treatment and making lifestyle changes as soon as possible is essential to reduce the risk of further complications. Regular monitoring of liver health and consultation with a physician is critical to successfully managing NAFLD. The system is innovative and cutting-edge, offering scalability and flexibility to easily adapt to different user needs.