What ML algorithms are used in healthcare industry? What are the most popular according to PubMed ?
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Samirnuri
ML algorithms chiefly extract features from data, such as patients’ “traits” and medical outcomes of interest. For a long time, AI in healthcare was dominated by the logistic regression, the most simple and common algorithm when it is necessary to classify things. It was easy to use, quick to finish and easy to interpret. However, in the past years the situation has changed and SVM and neural networks have taken the lead.
mohamed khamis ahmed
Artificial intelligence (AI) aims to mimic human cognitive functions. It is bringing a paradigm shift to healthcare, powered by increasing availability of healthcare data and rapid progress of analytics techniques. We survey the current status of AI applications in healthcare and discuss its future. AI can be applied to various types of healthcare data (structured and unstructured). Popular AI techniques include machine learning methods for structured data, such as the classical support vector machine and neural network, and the modern deep learning, as well as natural language processing for unstructured data. Major disease areas that use AI tools include cancer, neurology and cardiology. We then review in more details the AI applications in stroke, in the three major areas of early detection and diagnosis, treatment, as well as outcome prediction and prognosis evaluation. We conclude with discussion about pioneer AI systems, such as IBM Watson, and hurdles for real-life deployment of AI.