Machine learning insights concerning inflammatory and liver-related risk comorbidities in non-communicable and viral diseases

Abstract

The liver is a key organ involved in a wide range of functions, whose damage can lead to chronic liver disease (CLD). CLD accounts for more than two million deaths worldwide, becoming a social and economic burden for most countries. Among the different factors that can cause CLD, alcohol abuse, viruses, drug treatments, and unhealthy dietary patterns top the list. These conditions prompt and perpetuate an inflammatory environment and oxidative stress imbalance that favor the development of hepatic fibrogenesis. High stages of fibrosis can eventually lead to cirrhosis or hepatocellular carcinoma (HCC). Despite the advances achieved in this field, new approaches are needed for the prevention, diagnosis, treatment, and prognosis of CLD. In this context, the scientific com-munity is using machine learning (ML) algorithms to integrate and process vast amounts of data with unprecedented performance. ML techniques allow the integration of anthropometric, genetic, clinical, biochemical, dietary, lifestyle and omics data, giving new insights to tackle CLD and bringing personalized medicine a step closer. This review summarizes the investigations where ML techniques have been applied to study new approaches that could be used in inflammatory-related, hepatitis viruses-induced, and coronavirus disease 2019-induced liver damage and enlighten the factors involved in CLD development.

Multipanel Approach including miRNAs, Inflammatory Markers, and Depressive Symptoms for Metabolic Dysfunction-Associated Steatotic Liver Disease Diagnosis during 2-Year Nutritional Intervention

“…Inflammation plays a key role in MASLD, underscoring the importance of pursuing strategies aimed at reducing it [ 49 , 50 ]. Lifestyle interventions, such as hypocaloric diets based on the Mediterranean pattern, are highly effective and result in a reduction in proinflammatory markers [ 51 ], such as leptin and RBP4, as our results showed.…”

Integration of artificial intelligence in clinical laboratory medicine: Advancements and challenges

“…Regrettably, liver-related diseases persist in imposing a substantial social and economic burden on numerous countries, leading to the loss of numerous lives each year. 99 Most alterations in liver disease are ascribed to a prolonged state of inflammation and an imbalance in oxidative stress. This imbalance fosters the progression of liver fibrosis (HF), which can ultimately lead to cirrhosis, or HCC.…”

“…This imbalance fosters the progression of liver fibrosis (HF), which can ultimately lead to cirrhosis, or HCC. 99 Nowadays, ML plays a significant role in assessing the risks associated with liver diseases. Serra-Burriel and colleagues 100 developed an early LiverRisk score utilizing the results of six routine tests aspartate transferase, alanine transaminase, gamma-glutamyl transferase, glucose, cholesterol, and platelet count) along with patient age and gender information.…”

“…The liver plays a pivotal role in a wide array of metabolic processes in the body. Regrettably, liver‐related diseases persist in imposing a substantial social and economic burden on numerous countries, leading to the loss of numerous lives each year 99 . Most alterations in liver disease are ascribed to a prolonged state of inflammation and an imbalance in oxidative stress.…”

Heterogeneity in the response to n-3 polyunsaturated fatty acids

“…Perhaps background levels of EPA and DHA or the response to these fatty acids will also vary within each subpopulation of subjects with diabetes. Future studies using machine-learning approaches, as demonstrated in other disciplines, in the context of experiments with EPA/DHA will assist in moving the field forward [41][42][43][44].…”