Healthcare and Life Sciences
The combination of increasingly powerful computers and AI offers the possibility to be able to detect, diagnose, and cure diseases like never before. At IBM Research, we’re working on creating software and AI systems that can convert reams of health data into useable information for clinicians the world over.
Our work
IBM and Cleveland Clinic unveil the first quantum computer dedicated to healthcare research
NewsMike Murphy and Bethany Douglas- Accelerated Discovery
- Healthcare
- Quantum
IBM Research and JDRF continue to advance biomarker discovery research
Technical noteEileen Koski, Kenney Ng, Vibha Anand, Jianying Hu, and Mohamed Ghalwash- Healthcare
- Life Sciences
Accelerating discoveries in immunotherapy and disease treatment
Technical noteSara Capponi- Accelerated Discovery
- AI
- Healthcare
Why now is the time to accelerate discoveries in health care
NewsSolomon Assefa, Ajay Royyuru, Jianying Hu, Michal Rosen-Zvi, William Ogallo, and Kommy Weldemariam- Accelerated Discovery
- Healthcare
IBM is partnering with the Oxford Pandemic Sciences Institute
NewsAnthony Annunziata and Jason Crain- AI
- Healthcare
Computer simulations identify new ways to boost the skin’s natural protectors
ResearchJason Crain5 minute read- Accelerated Discovery
- Healthcare
- Materials Discovery
- Physical Sciences
- See more of our work on Healthcare and Life Sciences
Projects
CellCycleTRACER
Publications
- Mykhaylo Zayats
- Christopher Hansen
- et al.
- 2023
- MICCAI 2023
- 2023
- ICDH 2023
- Xi Yang
- Ge Gao
- et al.
- 2023
- IJCAI 2023
- Girmaw Abebe Tadesse
- Celia Cintas
- et al.
- 2023
- npj Digital Medicine
- 2023
- ACS Fall 2023
- Rémy Cochereau
- Viviana Maffeis
- et al.
- 2023
- Advanced Functional Materials
Research leads IBM’s response to COVID-19
To meet the global challenge of COVID-19, the world must come together. IBM has resources to share — like supercomputing power, virus tracking systems, and an AI assistant to answer citizens’ questions.
Tools + code
CLaSS: Controlled Latent attribute Space Sampling
Code for an efficient computational method for attribute-controlled generation of molecules, which leverages guidance from classifiers trained on an informative latent space of molecules modeled using a deep generative autoencoder.
View project →Peptide Walker
A visual platform for exploring the peptide space, modeled by our state-of-the-art peptide autoencoder.
View project →