Joint replacementReplacement arthroplasty (from Greek arthron, joint, limb, articulate, + plassein, to form, mould, forge, feign, make an image of), or joint replacement surgery, is a procedure of orthopedic surgery in which an arthritic or dysfunctional joint surface is replaced with an orthopedic prosthesis. Joint replacement is considered as a treatment when severe joint pain or dysfunction is not alleviated by less-invasive therapies. It is a form of arthroplasty, and is often indicated from various joint diseases, including osteoarthritis and rheumatoid arthritis.
Complications of pregnancyComplications of pregnancy are health problems that are related to, or arise during pregnancy. Complications that occur primarily during childbirth are termed obstetric labor complications, and problems that occur primarily after childbirth are termed puerperal disorders. While some complications improve or are fully resolved after pregnancy, some may lead to lasting effects, morbidity, or in the most severe cases, maternal or fetal mortality. Common complications of pregnancy include anemia, gestational diabetes, infections, gestational hypertension and pre-eclampsia.
Complications of diabetesComplications of diabetes mellitus include problems that develop rapidly (acute) or over time (chronic) and may affect many organ systems. The complications of diabetes can dramatically impair quality of life and cause long-lasting disability. Overall, complications are far less common and less severe in people with well-controlled blood sugar levels. Some non-modifiable risk factors such as age at diabetes onset, type of diabetes, gender and genetics may influence risk.
Complication (medicine)A complication in medicine, or medical complication, is an unfavorable result of a disease, health condition, or treatment. Complications may adversely affect the prognosis, or outcome, of a disease. Complications generally involve a worsening in the severity of the disease or the development of new signs, symptoms, or pathological changes that may become widespread throughout the body and affect other organ systems. Thus, complications may lead to the development of new diseases resulting from previously existing diseases.
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.
Perioperative mortalityPerioperative mortality has been defined as any death, regardless of cause, occurring within 30 days after surgery in or out of the hospital. Globally, 4.2 million people are estimated to die within 30 days of surgery each year. An important consideration in the decision to perform any surgical procedure is to weigh the benefits against the risks. Anesthesiologists and surgeons employ various methods in assessing whether a patient is in optimal condition from a medical standpoint prior to undertaking surgery, and various statistical tools are available.
ArthroscopyArthroscopy (also called arthroscopic or keyhole surgery) is a minimally invasive surgical procedure on a joint in which an examination and sometimes treatment of damage is performed using an arthroscope, an endoscope that is inserted into the joint through a small incision. Arthroscopic procedures can be performed during ACL reconstruction. The advantage over traditional open surgery is that the joint does not have to be opened up fully.
ArthroplastyArthroplasty (literally "[re-]forming of joint") is an orthopedic surgical procedure where the articular surface of a musculoskeletal joint is replaced, remodeled, or realigned by osteotomy or some other procedure. It is an elective procedure that is done to relieve pain and restore function to the joint after damage by arthritis or some other type of trauma. Joint replacement For the last 45 years, the most successful and common form of arthroplasty is the surgical replacement of arthritic or destructive or necrotic joint or joint surface with a prosthesis.
DataIn common usage and statistics, data (USˈdætə; UKˈdeɪtə) is a collection of discrete or continuous values that convey information, describing the quantity, quality, fact, statistics, other basic units of meaning, or simply sequences of symbols that may be further interpreted formally. A datum is an individual value in a collection of data. Data is usually organized into structures such as tables that provide additional context and meaning, and which may themselves be used as data in larger structures.
SurgerySurgery is a medical specialty that uses manual and/or instrumental techniques to physically reach into a subject's body in order to investigate or treat pathological conditions such as a disease or injury, to alter bodily functions (e.g. bariatric surgery such as gastric bypass), to improve appearance (cosmetic surgery), or to remove/replace unwanted tissues (body fat, glands, scars or skin tags) or foreign bodies. The subject receiving the surgery is typically a person (i.e. a patient), but can also be a non-human animal (i.
Predictive analyticsPredictive analytics is a form of business analytics applying machine learning to generate a predictive model for certain business applications. As such, it encompasses a variety of statistical techniques from predictive modeling and machine learning that analyze current and historical facts to make predictions about future or otherwise unknown events. It represents a major subset of machine learning applications; in some contexts, it is synonymous with machine learning.
Orthopedic surgeryOrthopedic surgery or orthopedics (alternatively spelt orthopaedics) is the branch of surgery concerned with conditions involving the musculoskeletal system. Orthopedic surgeons use both surgical and nonsurgical means to treat musculoskeletal trauma, spine diseases, sports injuries, degenerative diseases, infections, tumors, and congenital disorders. Nicholas Andry coined the word in French as orthopédie, derived from the Ancient Greek words ὀρθός orthos ("correct", "straight") and παιδίον paidion ("child"), and published Orthopedie (translated as Orthopædia: Or the Art of Correcting and Preventing Deformities in Children) in 1741.
Predictive modellingPredictive modelling uses statistics to predict outcomes. Most often the event one wants to predict is in the future, but predictive modelling can be applied to any type of unknown event, regardless of when it occurred. For example, predictive models are often used to detect crimes and identify suspects, after the crime has taken place. In many cases, the model is chosen on the basis of detection theory to try to guess the probability of an outcome given a set amount of input data, for example given an email determining how likely that it is spam.
OsteoarthritisOsteoarthritis (OA) is a type of degenerative joint disease that results from breakdown of joint cartilage and underlying bone which affects 1 in 7 adults in the United States. It is believed to be the fourth leading cause of disability in the world. The most common symptoms are joint pain and stiffness. Usually the symptoms progress slowly over years. Other symptoms may include joint swelling, decreased range of motion, and, when the back is affected, weakness or numbness of the arms and legs.
Rotator cuff tearRotator cuff tendinopathy is a process of senescence. The pathophysiology is mucoid degeneration. Most people develop rotator cuff tendinopathy within their lifetime. As part of rotator cuff tendinopathy, the tendon can thin and develop a defect. This defect is often referred to as a rotator cuff tear. Acute, traumatic rupture of the rotator cuff tendons can also occur, but is less common. Traumatic rupture of the rotator cuff usually involves the tendons of more than one muscle.
Binary classificationBinary classification is the task of classifying the elements of a set into two groups (each called class) on the basis of a classification rule. Typical binary classification problems include: Medical testing to determine if a patient has certain disease or not; Quality control in industry, deciding whether a specification has been met; In information retrieval, deciding whether a page should be in the result set of a search or not. Binary classification is dichotomization applied to a practical situation.
Support vector machineIn machine learning, support vector machines (SVMs, also support vector networks) are supervised learning models with associated learning algorithms that analyze data for classification and regression analysis. Developed at AT&T Bell Laboratories by Vladimir Vapnik with colleagues (Boser et al., 1992, Guyon et al., 1993, Cortes and Vapnik, 1995, Vapnik et al., 1997) SVMs are one of the most robust prediction methods, being based on statistical learning frameworks or VC theory proposed by Vapnik (1982, 1995) and Chervonenkis (1974).
Boosting (machine learning)In machine learning, boosting is an ensemble meta-algorithm for primarily reducing bias, and also variance in supervised learning, and a family of machine learning algorithms that convert weak learners to strong ones. Boosting is based on the question posed by Kearns and Valiant (1988, 1989): "Can a set of weak learners create a single strong learner?" A weak learner is defined to be a classifier that is only slightly correlated with the true classification (it can label examples better than random guessing).
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.
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.
