All types of healthcare organizations are explore different opportunities with software companies to develop administrative systems. As well as, with researchers to work out a multiple upcoming solutions that can ultimately aid in detecting diseases, diagnosing and treating an illness.
Machine Learning and Big Data
Big data, Artificial Intelligence (AI) and data science were recently implemented to process information. Machine learning (ML) was further introduced as a sub field of AI, that builds and trains programs using past data to predict the future. The whole concept of ML is to use pattern recognition so the computer can acquire data without being programmed precisely for specific tasks or with little human interaction. ML can further be split into three subsets: supervised, semi-supervised and unsupervised learning.
ML is widely used for numerous objectives within the medical field
- Detection in medical imaging and breath analysis
- Classification and Diagnosis of diseases
- Robotic surgical tools
- Developing drugs
Most Used ML Technique
Amongst ML techniques, Deep Neural Networks (DNN) is tremendously used for mathematical manipulation, pattern recognition and filtering, especially in the medical field. The human brain is able to do these activities at a rapid speed. Thus, with the utilization of weights and many layers, DNN has the ability to mimic the human brain. The technique takes in data and trains and tests the network by passing it through several layers. Each of the filters conveyed as layers are recognized as feature identifiers. Feature identifiers are attributes that help classify and detect certain features in a certain dataset, for the different usages.