Decision treeA decision tree is a decision support hierarchical model that uses a tree-like model of decisions and their possible consequences, including chance event outcomes, resource costs, and utility. It is one way to display an algorithm that only contains conditional control statements. Decision trees are commonly used in operations research, specifically in decision analysis, to help identify a strategy most likely to reach a goal, but are also a popular tool in machine learning.
Random forestRandom forests or random decision forests is an ensemble learning method for classification, regression and other tasks that operates by constructing a multitude of decision trees at training time. For classification tasks, the output of the random forest is the class selected by most trees. For regression tasks, the mean or average prediction of the individual trees is returned. Random decision forests correct for decision trees' habit of overfitting to their training set.
Decision tree learningDecision tree learning is a supervised learning approach used in statistics, data mining and machine learning. In this formalism, a classification or regression decision tree is used as a predictive model to draw conclusions about a set of observations. Tree models where the target variable can take a discrete set of values are called classification trees; in these tree structures, leaves represent class labels and branches represent conjunctions of features that lead to those class labels.
Fatty liver diseaseFatty liver disease (FLD), also known as hepatic steatosis, is a condition where excess fat builds up in the liver. Often there are no or few symptoms. Occasionally there may be tiredness or pain in the upper right side of the abdomen. Complications may include cirrhosis, liver cancer, and esophageal varices. There are two types of fatty liver disease: non-alcoholic fatty liver disease (NAFLD) and alcoholic liver disease. NAFLD is made up of simple fatty liver and non-alcoholic steatohepatitis (NASH).
Multi-armed banditIn probability theory and machine learning, the multi-armed bandit problem (sometimes called the K- or N-armed bandit problem) is a problem in which a fixed limited set of resources must be allocated between competing (alternative) choices in a way that maximizes their expected gain, when each choice's properties are only partially known at the time of allocation, and may become better understood as time passes or by allocating resources to the choice. This is a classic reinforcement learning problem that exemplifies the exploration–exploitation tradeoff dilemma.
Statistical classificationIn statistics, classification is the problem of identifying which of a set of categories (sub-populations) an observation (or observations) belongs to. Examples are assigning a given email to the "spam" or "non-spam" class, and assigning a diagnosis to a given patient based on observed characteristics of the patient (sex, blood pressure, presence or absence of certain symptoms, etc.). Often, the individual observations are analyzed into a set of quantifiable properties, known variously as explanatory variables or features.
Non-alcoholic fatty liver diseaseMetabolic (dysfunction) associated fatty liver disease (MAFLD) was previously known as non-alcoholic fatty liver disease (NAFLD) until renamed in 2023 by a global consensus panel composed mostly of hepatology researchers and clinicians. The term metabolic dysfunction-associated steatotic liver disease (MASLD) is also used. MAFLD is excessive fat build-up in the liver without another clear cause such as alcohol use.
Multi-agent systemA multi-agent system (MAS or "self-organized system") is a computerized system composed of multiple interacting intelligent agents. Multi-agent systems can solve problems that are difficult or impossible for an individual agent or a monolithic system to solve. Intelligence may include methodic, functional, procedural approaches, algorithmic search or reinforcement learning. Despite considerable overlap, a multi-agent system is not always the same as an agent-based model (ABM).
Biomarker (medicine)In medicine, a biomarker is a measurable indicator of the severity or presence of some disease state. It may be defined as a "cellular, biochemical or molecular alteration in cells, tissues or fluids that can be measured and evaluated to indicate normal biological processes, pathogenic processes, or pharmacological responses to a therapeutic intervention." More generally a biomarker is anything that can be used as an indicator of a particular disease state or some other physiological state of an organism.
Supervised learningSupervised learning (SL) is a paradigm in machine learning where input objects (for example, a vector of predictor variables) and a desired output value (also known as human-labeled supervisory signal) train a model. The training data is processed, building a function that maps new data on expected output values. An optimal scenario will allow for the algorithm to correctly determine output values for unseen instances. This requires the learning algorithm to generalize from the training data to unseen situations in a "reasonable" way (see inductive bias).
Clinical study designClinical study design is the formulation of trials and experiments, as well as observational studies in medical, clinical and other types of research (e.g., epidemiological) involving human beings. The goal of a clinical study is to assess the safety, efficacy, and / or the mechanism of action of an investigational medicinal product (IMP) or procedure, or new drug or device that is in development, but potentially not yet approved by a health authority (e.g. Food and Drug Administration).
Primary biliary cholangitisPrimary biliary cholangitis (PBC), previously known as primary biliary cirrhosis, is an autoimmune disease of the liver. It results from a slow, progressive destruction of the small bile ducts of the liver, causing bile and other toxins to build up in the liver, a condition called cholestasis. Further slow damage to the liver tissue can lead to scarring, fibrosis, and eventually cirrhosis. Common symptoms are tiredness, itching, and in more advanced cases, jaundice. In early cases, the only changes may be those seen in blood tests.
