Artificial Intelligence and Machine Learning
Artificial Intelligence, Machine Learning, and Deep Learning nowadays started playing a very effective and important role resulting in a great impact on various domains. These fields have been used in all areas as Data scientists realized that with the strength and power of rapidly growing data. The data shared by people of all ages in almost all social media handlers are of different types and in huge volume. This data consists of various kinds of information related to almost all domains. Data analysts know the power of this data and they introduced various techniques to get fruitful hidden insights from the data to benefit various organizations.
Algorithms used by Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL) started impacting the day-to-day life of society and have a dominant influence in almost all industries. Various disciplines in which AI and Machine Learning are playing very important Roles are Education, Medical, Agriculture, Manufacturing, Aeronautical, Big organizations like Bank, Scientific Applications, and many more.
The Health Care industry get influenced by these technologies most. Medical Science is one of the major areas where the ML and DL algorithms are used to diagnose various diseases so that patients can be treated well and in advance. Researchers use AI and ML in medical applications such as EEG analysis and Cancer Detection/Analysis
Advancements in technologies especially in the area of Artificial Intelligence, Machine Learning, and Deep Learning have paved the path to Health Care Industry. There are so many powerful Diagnosis Tools that use the available data sets to detect Cancer at early stages.
The biological datasets of DNA Methylation and RNA sequencing are used nowadays to examine it which helps to know about the genes. It can help doctors and analysts to know which all genes cause cancer and which all are able to suppress its expressions.
In the above picture, it is clear that ML and NLP are the subsets of AI, DL is the subset of ML. Various neural network base algorithms are developed in ML. These Algorithms allow the machine to learn in different ways and resolve the problems in the same manner as our human brain does. Deep Learning (DL) basically works like the human brain. It has the ability to process the data and to identify different images, various objects. DL can also process languages and help humans to take appropriate decisions to improve drug discovery, upgrade precision medicines, and improve the diagnosis of various diseases.
Deep Learning uses Artificial Neural Networks to process various medical Images to diagnose further. The Process of Artificial Neural Networks impersonates the human neural architecture. To enhance the processing power of Machine Learning, ANN is used which is basically consists of various inputs, generates output, and various hidden multi-layer networks.
There are various ways to diagnose different types of cancers in patients. To understand different types of algorithms, which can be used to diagnose different types of cancer, understand Machine Learning and AI along with various types of algorithms used to perform analysis.
2 Role of AI, ML and Deep Learning in Health Industry for Cancer Detection
Mathematical Models of Artificial Intelligence have the ability to understand human cognitive abilities. This feature easily handles the healthcare challenges like complex biological abnormalities that exist in cancer. The role of AI Technologies has played a very important role and this exponential growth of technologies AI-assisted us to make effective and optimal decisions. The super-intelligence these technologies use has overcome the issues of challenging areas where the human mind is limited to processing huge data within a fraction of seconds. AI has helped to diagnose Cancer disease by using AI-Based Algorithms to identify complex and multifaced disorders with thousands of genetic and epigenetic variations. Different AI algorithms help to identify these complex and large number of genetic mutations and aberrant protein interactions at a very early stage. Modern biomedical research is working so hard to bring AI technology to assist pathologists and physicians also. These technologies enable them to predict any disease risk, diagnose it minutely, and suggest effective treatments on time. Researchers are digitally collaborating in real-time to diagnose Cancer and provide treatments to heal millions of people. are continuously using Machine Learning, AI-based system approach for Clinical Applications, researchers can collaborate in real-time and share knowledge digitally to potentially heal millions. Researchers contribute their knowledge in this area and help oncologists so that they can give precise treatment to every individual in the future.
Classification accuracy of deep learning classifiers is largely dependent on the quality and size of the datasets. Deep learning requires a massive amount of medical imaging training datasets to give precise and successful results. The biggest challenge in the success of deep learning is the unavailability of an enormous amount of datasets.
Dr. Arpana Chaturvedi
HOD-BCA Department of Information Technology
