Remove Big Data Remove Engineer Remove Life Science
article thumbnail

The case for AI and machine learning in life sciences

Pharmaceutical Technology

The current tech landscape is rapidly evolving, with advancements in areas such as big data and conversational platforms. Most of us have heard of ChatGPT and AI but where and how do they fit into the life sciences ecosystem? Content input to these platforms become part of the engines and can be used publicly.

article thumbnail

Synthetic control arms in clinical trials: Making it happen

pharmaphorum

David Clifton is professor of clinical machine learning in the Department of Engineering Science of the University of Oxford. He is also a research fellow of the Royal Academy of Engineering and a fellow of the Alan Turing Institute. Since 2008, he has translated his work into the biomedical context for healthcare applications.

Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

Revolutionizing Medicine and Public Health: The Emergence of Big Data in Healthcare

Roots Analysis

Big Data in healthcare refers to the vast amount of data that is continuously expanding and cannot be efficiently stored or processed using traditional tools. It accounts for the majority of big data in healthcare and comprises information, such as medical images, surveys, chats, and written narratives.

article thumbnail

New technologies fuel advancements in digital health

Pharmaceutical Technology

Services such as Personal Health Records and diagnostic apps collect, store and analyse patient data, which assists healthcare practitioners with diagnosis as well as enabling them to create tailored treatment plans based on the needs of the patient. Hamilton: Canada’s emerging leader in life sciences research and commercialization.

article thumbnail

Empowering rare disease patient advocacy organisations with data

pharmaphorum

Sun says because of this, Komodo engineered solutions or apps that “do certain things for end-users applied against the Healthcare Map.”. Therefore, organisations can determine how they’d like to use the Map’s data then create a software solution that helps them do so. About the author.

article thumbnail

Bioinformatics Jobs: How to Succeed in This Competitive Space

XTalks

The minimum requirement to become a professional in the bioinformatics field includes having a bachelor’s and master’s degree in bioinformatics, computer engineering, computational biology, computer science, or related field. Bioinformatics Engineer. How to Become a Bioinformatics Engineer. Job Description.

article thumbnail

Genmab’s Silver Anniversary: Reflecting on 25 Years of Breakthroughs in Antibody Therapeutics

XTalks

First, the integration of AI, big data and high-performance computing has the potential to not only expedite the drug discovery process, but also could contribute to better understanding of diseases at the molecular level. Tahi Ahmadi: Two key areas where we anticipate breakthroughs are technological advancements and new modalities.