Big Data in Oncology: Impact, Challenges, and Risk Assessment (River Publishers Series in Biomedical Engineering) (Original PDF from Publisher)

Big Data in Oncology Impact Challenges and Risk Assessment

The age of large-scale science is upon us. Numerous data types, including transcriptomes, clinical data, cancer genomes, and more, are grouped together in oncology. Integrating all of the diverse data that has been gathered into a single, analytical platform that produces legible files is the difficulty of big data in cancer. Treatment and result for cancer patients are improved by the potential to use information from all the collected data. There are several aspects to resolving the big data issue in cancer. In order to control cancer, Big Data in Oncology: Impact, Challenges, and Risk Assessment integrates knowledge from cutting-edge information and communication technologies like artificial intelligence, data science, and big data analytics.

The use of big data analytics for targeted disease therapy is the main topic of this book. It offers details on the difficulties and uses of big data in cancer treatment, as well as focused treatment in oncology.

Current advancements in data analytics, computers, medical imaging, customized medicine, machine learning, and artificial intelligence for better patient care.
An explanation of how big data and AI are being used to find novel cancer treatment targets.

An overview of various big data-based risk assessments in the field of cancer.
Pay attention to oncology dose prediction utilizing big data.

Academics, research researchers, medical professionals, hospital administrators, pharmaceutical chemists, the biomedical sector, software developers, and IT specialists are the most specific or pertinent audience.