Page 1

Artificial Intelligence achieving dermatologist-level of identification Skin cancer is the destructive cancerous growth of the skin. Such growth originates from the superficial layer of the skin that is the epidermis. The majority of such skin cancer are less likely to spread to other parts of the body, unlike malignant melanoma. This is the most common human malignancy that can be primarily diagnosed visually. According to the latest research that attempts to apply artificial intelligence to health, computers are now able to classify skin cancers as effectively as a human expert. Artificial intelligence is the theory and development of computer systems that will be able to perform the tasks of human intelligence. These computer systems will be able to carry out tasks such as visual perception, decision-making, speech recognition and translation of languages.


Even though the term artificial intelligence has come into existence in the year 1956, it has become popular today because of a number of factors such as increased data volumes, progressive algorithms and the improvements in computing power and storage. According to US-based researchers, the new system that has been developed based on image recognition can also be developed for smartphones thereby increasing access for screening and ultimately providing a low-cost way to check if skin-lesions are a cause for concern. The technology of Artificial Intelligence is developed at the University of Waterloo mainly to detect melanoma skin cancer. Machine-learning software is used by this technology so that images of skin lesions can be analyzed. This analysis will provide objective data to doctors on biological makers that will help in the early detection of the disease for which treatment can be started. Late detection of skin cancer is serious and can be life-threatening. The incidence of malignant melanoma has been increasing and it is estimated that almost 232000 news cases are showing. The skin cancer can be treated when it is detected early. Use in different sectors: There is high demand for Artificial intelligence in most of the industries. The question answering system can be used for legal assistance, patent searches and medical research. Some of the uses of Artificial Intelligence includes the following. Healthcare: The applications will be able to provide personalized medicine and Xray readings. The personal healthcare assistants act as life-coaches and remind individuals to take the pills on time. Manufacturing: The factory data can only be analyzed Artificial Intelligence so that the expected load and demand can be estimated.


Retail: Virtual shopping experience is possible through Artificial intelligence that offers personalized recommendations and discusses purchase options. There are a few technologies that enable and support artificial intelligence and these are: Graphical processing units: These are key to artificial intelligence because they are the source of heavy compute power that is required for interactive processing. Application Processing Interfaces: These are portable packages of code that ensures that artificial intelligence can be added to existing products and packages. The World Health Organization reported that one in every three cancers worldwide is skin cancer. During the year 2014, 131772 cases of UK showed no-melanoma skin cancer. As reported by the Cancer Research UK, during the year 2014 there were almost 15419 cases of melanoma, the deadliest skin cancer, thereby making it the fifth most common cancer. A team from the United States, Germany and France programmed an artificial intelligence system to differentiate between dangerous skin lesions from the benign ones and this was done by showing 100000 images. This machine, that was named the convolutional neural network, was then tested in 17 countries against a number of dermatologists by showing photos of malignant melanomas and benign moles. Half of the dermatologist who was tested was at the expert level with more than five years of experience, 19% had experience of two to five years and 29% were beginners with experience of not more than two years. According to the research team, most of these dermatologists were surpassed by the CNN. On an average, the dermatologists were able to detect 86.6% of skin cancers as compared to 95% for the CNN. One of the authors of the study showed that CNN missed a few spots and it is mainly due to higher sensitivity.


Such findings show that this characteristic of high sensitivity of CNN than the dermatologists is posing as a problem and therefore it is not able to diagnose few malignant melanomas that means that there is higher specificity which will ultimately eliminate unnecessary surgeries. These results also show that the dermatologists including trained experts are being out-run by deep learning convolutional networks. Importance of artificial intelligence: The importance of artificial intelligence can be explained with the following points. Repetitive learning and discovery through data: Artificial Intelligence perform frequent and high-volume tasks without fatigue. Adds intelligence: Intelligence is added to existing products and it is not sold as an individual application. The products already in use will be modified. Adaptations through progressive learning technique: It lets the data do the programming. The technique either becomes the classifier and the predictor. Analysis of a large number of deeper data: Building fake detection system that has five hidden layers is only possible because of Artificial Intelligence. This can be used to find cancer on MRIs that too with accuracy equal to that of trained radiologists. The most outcome of the data: The data are easily converted into intellectual property and it also helps in creating a competitive advantage in a competitive industry. PatientMD

platform uses this technology to its best where it scan a lesion through its

advanced machine learning script and compares it with its pre trained images to


look if the user is developing any kind of skin concern. If the results come positive he will be guided to a dermatologist for future course of action. However, as pointed out by Dr Victoria Mar of Monash University in Melbourne, Australia, and Professor H. Peter Soyer from the University of Queensland in Brisbane, there would be a number of issues and those need to be corrected before artificial intelligence can be used in clinics. For example, there would be a difficulty in examining some melanomas on the fingers, toes and scalp. They also pointed out that is a difficulty in training artificial intelligence about atypical melanomas that patients are not even aware of. They also concluded that clinical examination cannot be substituted and there is much more work to be done before this technology can be implemented. They also stated that sooner than later, the diagnostic pattern in dermatology will get changed by automated diagnosis.

Artificial Intelligence achieving dermatologist-level of identification  
Artificial Intelligence achieving dermatologist-level of identification  
Advertisement