Classic autism_Infantile autism Classic autism, also known as childhood autism, autistic disorder, (early) infantile autism, infantile psychosis, Kanner's autism, Kanner's syndrome, or (formerly) just autism, is a neurodevelopmental condition first described by Leo Kanner in 1943. It is characterized by atypical and impaired development in social interaction and communication as well as restricted, repetitive behaviors, activities, and interests. These symptoms first appear in early childhood and persist throughout life.
Machine learningMachine learning (ML) is an umbrella term for solving problems for which development of algorithms by human programmers would be cost-prohibitive, and instead the problems are solved by helping machines 'discover' their 'own' algorithms, without needing to be explicitly told what to do by any human-developed algorithms. Recently, generative artificial neural networks have been able to surpass results of many previous approaches.
Industrial wastewater treatmentIndustrial wastewater treatment describes the processes used for treating wastewater that is produced by industries as an undesirable by-product. After treatment, the treated industrial wastewater (or effluent) may be reused or released to a sanitary sewer or to a surface water in the environment. Some industrial facilities generate wastewater that can be treated in sewage treatment plants.
DysthymiaDysthymia (dɪsˈθaɪmiə ), also known as persistent depressive disorder (PDD), is a mental and behavioral disorder, specifically a disorder primarily of mood, consisting of similar cognitive and physical problems as major depressive disorder, but with longer-lasting symptoms. The concept was used by Robert Spitzer as a replacement for the term "depressive personality" in the late 1970s. In the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV), dysthymia is a serious state of chronic depression, which persists for at least two years (one year for children and adolescents).
Seasonal affective disorderSeasonal affective disorder (SAD) is a mood disorder subset in which people who typically have normal mental health throughout most of the year exhibit depressive symptoms at the same time each year. It is commonly, but not always, associated with the reductions in total daily sunlight hours that occur during the summer or winter. Common symptoms include sleeping too much, having little to no energy, and overeating. The condition in the summer can include heightened anxiety.
Online machine learningIn computer science, online machine learning is a method of machine learning in which data becomes available in a sequential order and is used to update the best predictor for future data at each step, as opposed to batch learning techniques which generate the best predictor by learning on the entire training data set at once. Online learning is a common technique used in areas of machine learning where it is computationally infeasible to train over the entire dataset, requiring the need of out-of-core algorithms.
Rule-based machine learningRule-based machine learning (RBML) is a term in computer science intended to encompass any machine learning method that identifies, learns, or evolves 'rules' to store, manipulate or apply. The defining characteristic of a rule-based machine learner is the identification and utilization of a set of relational rules that collectively represent the knowledge captured by the system. This is in contrast to other machine learners that commonly identify a singular model that can be universally applied to any instance in order to make a prediction.
Cross-validation (statistics)Cross-validation, sometimes called rotation estimation or out-of-sample testing, is any of various similar model validation techniques for assessing how the results of a statistical analysis will generalize to an independent data set. Cross-validation is a resampling method that uses different portions of the data to test and train a model on different iterations. It is mainly used in settings where the goal is prediction, and one wants to estimate how accurately a predictive model will perform in practice.
Pearson correlation coefficientIn statistics, the Pearson correlation coefficient (PCC) is a correlation coefficient that measures linear correlation between two sets of data. It is the ratio between the covariance of two variables and the product of their standard deviations; thus, it is essentially a normalized measurement of the covariance, such that the result always has a value between −1 and 1. As with covariance itself, the measure can only reflect a linear correlation of variables, and ignores many other types of relationships or correlations.
BrainA brain is an organ that serves as the center of the nervous system in all vertebrate and most invertebrate animals. It is located in the head, usually close to the sensory organs for senses such as vision. It is the most complex organ in a vertebrate's body. In a human, the cerebral cortex contains approximately 14–16 billion neurons, and the estimated number of neurons in the cerebellum is 55–70 billion. Each neuron is connected by synapses to several thousand other neurons.
Neuro-ophthalmologyNeuro-ophthalmology is an academically-oriented subspecialty that merges the fields of neurology and ophthalmology, often dealing with complex systemic diseases that have manifestations in the visual system. Neuro-ophthalmologists initially complete a residency in either neurology or ophthalmology, then do a fellowship in the complementary field. Since diagnostic studies can be normal in patients with significant neuro-ophthalmic disease, a detailed medical history and physical exam is essential, and neuro-ophthalmologists often spend a significant amount of time with their patients.
Training, validation, and test data setsIn machine learning, a common task is the study and construction of algorithms that can learn from and make predictions on data. Such algorithms function by making data-driven predictions or decisions, through building a mathematical model from input data. These input data used to build the model are usually divided into multiple data sets. In particular, three data sets are commonly used in different stages of the creation of the model: training, validation, and test sets.
