Cerebral edemaCerebral edema is excess accumulation of fluid (edema) in the intracellular or extracellular spaces of the brain. This typically causes impaired nerve function, increased pressure within the skull, and can eventually lead to direct compression of brain tissue and blood vessels. Symptoms vary based on the location and extent of edema and generally include headaches, nausea, vomiting, seizures, drowsiness, visual disturbances, dizziness, and in severe cases, coma and death.
Ridge regressionRidge regression is a method of estimating the coefficients of multiple-regression models in scenarios where the independent variables are highly correlated. It has been used in many fields including econometrics, chemistry, and engineering. Also known as Tikhonov regularization, named for Andrey Tikhonov, it is a method of regularization of ill-posed problems. It is particularly useful to mitigate the problem of multicollinearity in linear regression, which commonly occurs in models with large numbers of parameters.
Cerebral venous sinus thrombosisCerebral venous sinus thrombosis (CVST), cerebral venous and sinus thrombosis or cerebral venous thrombosis (CVT), is the presence of a blood clot in the dural venous sinuses (which drain blood from the brain), the cerebral veins, or both. Symptoms may include severe headache, visual symptoms, any of the symptoms of stroke such as weakness of the face and limbs on one side of the body, and seizures, which occur in around 40% of patients.
Cerebral arteriovenous malformationA cerebral arteriovenous malformation (cerebral AVM, CAVM, cAVM, brain AVM, or BAVM) is an abnormal connection between the arteries and veins in the brain—specifically, an arteriovenous malformation in the cerebrum. The most frequently observed problems related to a cerebral arteriovenous malformation (AVM) are headaches and seizures, cranial nerve afflictions including pinched nerve and palsy, backaches, neckaches, and nausea from coagulated blood that has made its way down to be dissolved in the cerebrospinal fluid.
Artificial neural networkArtificial neural networks (ANNs, also shortened to neural networks (NNs) or neural nets) are a branch of machine learning models that are built using principles of neuronal organization discovered by connectionism in the biological neural networks constituting animal brains. An ANN is based on a collection of connected units or nodes called artificial neurons, which loosely model the neurons in a biological brain. Each connection, like the synapses in a biological brain, can transmit a signal to other neurons.
Law of large numbersIn probability theory, the law of large numbers (LLN) is a theorem that describes the result of performing the same experiment a large number of times. According to the law, the average of the results obtained from a large number of trials should be close to the expected value and tends to become closer to the expected value as more trials are performed. The LLN is important because it guarantees stable long-term results for the averages of some random events.
Traumatic brain injuryA traumatic brain injury (TBI), also known as an intracranial injury, is an injury to the brain caused by an external force. TBI can be classified based on severity ranging from mild traumatic brain injury (mTBI/concussion) to severe traumatic brain injury. TBI can also be characterized based on mechanism (closed or penetrating head injury) or other features (e.g., occurring in a specific location or over a widespread area). Head injury is a broader category that may involve damage to other structures such as the scalp and skull.
Recurrent neural networkA recurrent neural network (RNN) is one of the two broad types of artificial neural network, characterized by direction of the flow of information between its layers. In contrast to uni-directional feedforward neural network, it is a bi-directional artificial neural network, meaning that it allows the output from some nodes to affect subsequent input to the same nodes. Their ability to use internal state (memory) to process arbitrary sequences of inputs makes them applicable to tasks such as unsegmented, connected handwriting recognition or speech recognition.
Linear discriminant analysisLinear discriminant analysis (LDA), normal discriminant analysis (NDA), or discriminant function analysis is a generalization of Fisher's linear discriminant, a method used in statistics and other fields, to find a linear combination of features that characterizes or separates two or more classes of objects or events. The resulting combination may be used as a linear classifier, or, more commonly, for dimensionality reduction before later classification.
Wetware computerA wetware computer is an organic computer (which can also be known as an artificial organic brain or a neurocomputer) composed of organic material "wetware" such as "living" neurons. Wetware computers composed of neurons are different than conventional computers because they use biological materials, and offer the possibility of substantially more energy-efficient computing. While a wetware computer is still largely conceptual, there has been limited success with construction and prototyping, which has acted as a proof of the concept's realistic application to computing in the future.
