Convolutional neural networkConvolutional neural network (CNN) is a regularized type of feed-forward neural network that learns feature engineering by itself via filters (or kernel) optimization. Vanishing gradients and exploding gradients, seen during backpropagation in earlier neural networks, are prevented by using regularized weights over fewer connections. For example, for each neuron in the fully-connected layer 10,000 weights would be required for processing an image sized 100 × 100 pixels.
Minimally invasive procedureMinimally invasive procedures (also known as minimally invasive surgeries) encompass surgical techniques that limit the size of incisions needed, thereby reducing wound healing time, associated pain, and risk of infection. Surgery by definition is invasive and many operations requiring incisions of some size are referred to as open surgery. Incisions made during open surgery can sometimes leave large wounds that may be painful and take a long time to heal.
Abdominal surgeryThe term abdominal surgery broadly covers surgical procedures that involve opening the abdomen (laparotomy). Surgery of each abdominal organ is dealt with separately in connection with the description of that organ (see stomach, kidney, liver, etc.) Diseases affecting the abdominal cavity are dealt with generally under their own names (e.g. appendicitis). The most common abdominal surgeries are described below. Appendectomy: surgical opening of the abdominal cavity and removal of the appendix.
AppendectomyAn appendectomy (American English), also known as an appendicectomy (British English), is a surgical operation in which the vermiform appendix (a portion of the intestine) is removed. Appendectomy is normally performed as an urgent or emergency procedure to treat complicated acute appendicitis. Appendectomy may be performed laparoscopically (as minimally invasive surgery) or as an open operation. Over the 2010s, surgical practice has increasingly moved towards routinely offering laparoscopic appendicectomy; for example in the United Kingdom over 95% of adult appendicectomies are planned as laparoscopic procedures.
UrologyUrology (from Greek οὖρον ouron "urine" and -λογία -logia "study of"), also known as genitourinary surgery, is the branch of medicine that focuses on surgical and medical diseases of the urinary-tract system and the reproductive organs. Organs under the domain of urology include the kidneys, adrenal glands, ureters, urinary bladder, urethra, and the male reproductive organs (testes, epididymis, vas deferens, seminal vesicles, prostate, and penis). The urinary and reproductive tracts are closely linked, and disorders of one often affect the other.
Plastic surgeryPlastic surgery is a surgical specialty involving the restoration, reconstruction or alteration of the human body. It can be divided into two main categories: reconstructive surgery and cosmetic surgery. Reconstructive surgery includes craniofacial surgery, hand surgery, microsurgery, and the treatment of burns. While reconstructive surgery aims to reconstruct a part of the body or improve its functioning, cosmetic (or aesthetic) surgery aims at improving the appearance of it.
TrocarA trocar (or trochar) is a medical or veterinary device used in minimally invasive surgery, typically made up of an awl (which may be a metal or plastic with a pointed or tapered tip), a cannula (essentially a rigid hollow tube) and often a seal, and some trocars also include a valve mechanism to allow for insufflation. Trocars are designed for placement through the chest and abdominal walls during thoracoscopic and laparoscopic surgery, and each trocar functions as a portal for the subsequent insertion of other endoscopic instruments such as grasper, scissors, stapler, electrocautery, suction tip, etc.
Types of artificial neural networksThere are many types of artificial neural networks (ANN). Artificial neural networks are computational models inspired by biological neural networks, and are used to approximate functions that are generally unknown. Particularly, they are inspired by the behaviour of neurons and the electrical signals they convey between input (such as from the eyes or nerve endings in the hand), processing, and output from the brain (such as reacting to light, touch, or heat). The way neurons semantically communicate is an area of ongoing research.
Gesture recognitionGesture recognition is a topic in computer science and language technology with the goal of interpreting human gestures via mathematical algorithms. It is a subdiscipline of computer vision. Gestures can originate from any bodily motion or state, but commonly originate from the face or hand. Focuses in the field include emotion recognition from face and hand gesture recognition since they are all expressions. Users can make simple gestures to control or interact with devices without physically touching them.
Activity recognitionActivity recognition aims to recognize the actions and goals of one or more agents from a series of observations on the agents' actions and the environmental conditions. Since the 1980s, this research field has captured the attention of several computer science communities due to its strength in providing personalized support for many different applications and its connection to many different fields of study such as medicine, human-computer interaction, or sociology.
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.
Robot-assisted surgeryRobot-assisted surgery or robotic surgery are any types of surgical procedures that are performed using robotic systems. Robotically assisted surgery was developed to try to overcome the limitations of pre-existing minimally-invasive surgical procedures and to enhance the capabilities of surgeons performing open surgery. In the case of robotically assisted minimally-invasive surgery, instead of the surgeon directly moving the instruments, the surgeon uses one of two methods to perform dissection, hemostasis and resection, using a direct telemanipulator, or through computer control.
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.
Residual neural networkA Residual Neural Network (a.k.a. Residual Network, ResNet) is a deep learning model in which the weight layers learn residual functions with reference to the layer inputs. A Residual Network is a network with skip connections that perform identity mappings, merged with the layer outputs by addition. It behaves like a Highway Network whose gates are opened through strongly positive bias weights. This enables deep learning models with tens or hundreds of layers to train easily and approach better accuracy when going deeper.
Computer visionComputer vision tasks include methods for , , and understanding digital images, and extraction of high-dimensional data from the real world in order to produce numerical or symbolic information, e.g. in the forms of decisions. Understanding in this context means the transformation of visual images (the input to the retina in the human analog) into descriptions of the world that make sense to thought processes and can elicit appropriate action.
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.
Machine visionMachine vision (MV) is the technology and methods used to provide -based automatic inspection and analysis for such applications as automatic inspection, process control, and robot guidance, usually in industry. Machine vision refers to many technologies, software and hardware products, integrated systems, actions, methods and expertise. Machine vision as a systems engineering discipline can be considered distinct from computer vision, a form of computer science.
Facial recognition systemA facial recognition system is a technology potentially capable of matching a human face from a or a video frame against a database of faces. Such a system is typically employed to authenticate users through ID verification services, and works by pinpointing and measuring facial features from a given image. Development began on similar systems in the 1960s, beginning as a form of computer application. Since their inception, facial recognition systems have seen wider uses in recent times on smartphones and in other forms of technology, such as robotics.
Cross-entropyIn information theory, the cross-entropy between two probability distributions and over the same underlying set of events measures the average number of bits needed to identify an event drawn from the set if a coding scheme used for the set is optimized for an estimated probability distribution , rather than the true distribution . The cross-entropy of the distribution relative to a distribution over a given set is defined as follows: where is the expected value operator with respect to the distribution .
Pattern recognitionPattern recognition is the automated recognition of patterns and regularities in data. While similar, pattern recognition (PR) is not to be confused with pattern machines (PM) which may possess (PR) capabilities but their primary function is to distinguish and create emergent pattern. PR has applications in statistical data analysis, signal processing, , information retrieval, bioinformatics, data compression, computer graphics and machine learning.
