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.
Convective storm detectionConvective storm detection is the meteorological observation, and short-term prediction, of deep moist convection (DMC). DMC describes atmospheric conditions producing single or clusters of large vertical extension clouds ranging from cumulus congestus to cumulonimbus, the latter producing thunderstorms associated with lightning and thunder. Those two types of clouds can produce severe weather at the surface and aloft.
Anomaly detectionIn data analysis, anomaly detection (also referred to as outlier detection and sometimes as novelty detection) is generally understood to be the identification of rare items, events or observations which deviate significantly from the majority of the data and do not conform to a well defined notion of normal behaviour. Such examples may arouse suspicions of being generated by a different mechanism, or appear inconsistent with the remainder of that set of data.
ProsthesisIn medicine, a prosthesis (: prostheses; from prósthesis), or a prosthetic implant, is an artificial device that replaces a missing body part, which may be lost through trauma, disease, or a condition present at birth (congenital disorder). Prostheses are intended to restore the normal functions of the missing body part. Amputee rehabilitation is primarily coordinated by a physiatrist as part of an inter-disciplinary team consisting of physiatrists, prosthetists, nurses, physical therapists, and occupational therapists.
AmputationAmputation is the removal of a limb by trauma, medical illness, or surgery. As a surgical measure, it is used to control pain or a disease process in the affected limb, such as malignancy or gangrene. In some cases, it is carried out on individuals as a preventive surgery for such problems. A special case is that of congenital amputation, a congenital disorder, where fetal limbs have been cut off by constrictive bands. In some countries, amputation is currently used to punish people who commit crimes.
Tornado vortex signatureA tornadic vortex signature, abbreviated TVS, is a Pulse-Doppler radar weather radar detected rotation algorithm that indicates the likely presence of a strong mesocyclone that is in some stage of tornadogenesis. It may give meteorologists the ability to pinpoint and track the location of tornadic rotation within a larger storm, and is one component of the National Weather Service's warning operations. The tornadic vortex signature was first identified by Donald W. Burgess, Leslie R. Lemon, and Rodger A.
Brain damageNeurotrauma, brain damage or brain injury (BI) is the destruction or degeneration of brain cells. Brain injuries occur due to a wide range of internal and external factors. In general, brain damage refers to significant, undiscriminating trauma-induced damage. A common category with the greatest number of injuries is traumatic brain injury (TBI) following physical trauma or head injury from an outside source, and the term acquired brain injury (ABI) is used in appropriate circles to differentiate brain injuries occurring after birth from injury, from a genetic disorder (GBI), or from a congenital disorder (CBI).
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.
Feature (machine learning)In machine learning and pattern recognition, a feature is an individual measurable property or characteristic of a phenomenon. Choosing informative, discriminating and independent features is a crucial element of effective algorithms in pattern recognition, classification and regression. Features are usually numeric, but structural features such as strings and graphs are used in syntactic pattern recognition. The concept of "feature" is related to that of explanatory variable used in statistical techniques such as linear regression.
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.
Sports injurySports injuries are injuries that occur during sport, athletic activities, or exercising. In the United States, there are approximately 30 million teenagers and children who participate in some form of organized sport. Of those, about three million athletes age 14 years and under experience a sports injury annually. According to a study performed at Stanford University, 21 percent of the injuries observed in elite college athletes caused the athlete to miss at least one day of sport, and approximately 77 percent of these injuries involved the knee, lower leg, ankle, or foot.
Head injuryA head injury is any injury that results in trauma to the skull or brain. The terms traumatic brain injury and head injury are often used interchangeably in the medical literature. Because head injuries cover such a broad scope of injuries, there are many causes—including accidents, falls, physical assault, or traffic accidents—that can cause head injuries. The number of new cases is 1.7 million in the United States each year, with about 3% of these incidents leading to death.
Automated machine learningAutomated machine learning (AutoML) is the process of automating the tasks of applying machine learning to real-world problems. AutoML potentially includes every stage from beginning with a raw dataset to building a machine learning model ready for deployment. AutoML was proposed as an artificial intelligence-based solution to the growing challenge of applying machine learning. The high degree of automation in AutoML aims to allow non-experts to make use of machine learning models and techniques without requiring them to become experts in machine learning.
PerceptronIn machine learning, the perceptron (or McCulloch-Pitts neuron) is an algorithm for supervised learning of binary classifiers. A binary classifier is a function which can decide whether or not an input, represented by a vector of numbers, belongs to some specific class. It is a type of linear classifier, i.e. a classification algorithm that makes its predictions based on a linear predictor function combining a set of weights with the feature vector.
Feature selectionFeature selection is the process of selecting a subset of relevant features (variables, predictors) for use in model construction. Stylometry and DNA microarray analysis are two cases where feature selection is used. It should be distinguished from feature extraction. Feature selection techniques are used for several reasons: simplification of models to make them easier to interpret by researchers/users, shorter training times, to avoid the curse of dimensionality, improve data's compatibility with a learning model class, encode inherent symmetries present in the input space.
Ensemble learningIn statistics and machine learning, ensemble methods use multiple learning algorithms to obtain better predictive performance than could be obtained from any of the constituent learning algorithms alone. Unlike a statistical ensemble in statistical mechanics, which is usually infinite, a machine learning ensemble consists of only a concrete finite set of alternative models, but typically allows for much more flexible structure to exist among those alternatives.
Primary and secondary brain injuryPrimary and secondary brain injury are ways to classify the injury processes that occur in brain injury. In traumatic brain injury (TBI), primary brain injury occurs during the initial insult, and results from displacement of the physical structures of the brain. Secondary brain injury occurs gradually and may involve an array of cellular processes. Secondary injury, which is not caused by mechanical damage, can result from the primary injury or be independent of it.
Computer-aided diagnosisComputer-aided detection (CADe), also called computer-aided diagnosis (CADx), are systems that assist doctors in the interpretation of medical images. Imaging techniques in X-ray, MRI, Endoscopy, and ultrasound diagnostics yield a great deal of information that the radiologist or other medical professional has to analyze and evaluate comprehensively in a short time. CAD systems process digital images or videos for typical appearances and to highlight conspicuous sections, such as possible diseases, in order to offer input to support a decision taken by the professional.
Physical therapyPhysical therapy (PT), also known as physiotherapy, is one of the allied health professions. It is provided by physical therapists who promote, maintain, or restore health through physical examination, diagnosis, management, prognosis, patient education, physical intervention, rehabilitation, disease prevention, and health promotion. Physical therapists are known as physiotherapists in many countries. The career has many specialties including musculoskeletal, orthopedics, cardiopulmonary, neurology, endocrinology, sports medicine, geriatrics, pediatrics, women's health, wound care and electromyography.
Learning classifier systemLearning classifier systems, or LCS, are a paradigm of rule-based machine learning methods that combine a discovery component (e.g. typically a genetic algorithm) with a learning component (performing either supervised learning, reinforcement learning, or unsupervised learning). Learning classifier systems seek to identify a set of context-dependent rules that collectively store and apply knowledge in a piecewise manner in order to make predictions (e.g. behavior modeling, classification, data mining, regression, function approximation, or game strategy).
