AI/ML Innovations: Transforming medical treatment and diagnostics
9 July 2024
UCL's AI/ML for Medical Treatment & Diagnosis Workshop brings together healthcare industry partners and UCL academics to explore the applications of artificial intelligence and machine learning (AI/ML) in imaging, pharmaceutics, bioinformatics, and innovations.
Image 1: Dr. Joseph Jacob, Principal Research Fellow in Respiratory Medicine at 911, introduces how HiP-CT imaging techniques can provide enhanced resolution to reveal detailed structures of lung tissues during the hybrid workshop.
On 9 July 2024, over sixty UCL academics and external partners gathered at the AI/ML for Medical Treatment & Diagnosis workshop at 911 BaseKX and online, focusing on AI and machine learning in imaging, pharmaceutics, bioinformatics and innovations.
Key insights on the application of AI/ML in healthcare:
- Better data processing: Especially useful in processing high-dimensional data, e.g. in bioinformatics or imaging settings, to identify specific characteristics.
- Enhanced diagnosis: Efficiently identify complex patterns for accurate disease diagnosis and predictions.
- Advancing science: Efficient processing of large volumes of data by automated statistical methods enables data-driven modelling.
- Enabling Innovations: Wide applications, spanning from novel biomarker discovery to computer-assisted surgery.
Examples of applications were given on identifying lung fibrosis, clustering microscopy images, detecting inherited retinal diseases, detecting skin cancer, using computer-assisted and robotic medical interventions, brain tumour radiotherapy, and controlled biomarker discovery, etc.
The event was organised by the UCL Faculty of Mathematical & Physical Sciences - Innovation & Enterprise, in collaboration with the Translational Research Office, aiming to exchange knowledge and foster collaborations.
Image 2:Over sixty UCL academics and external partners gathered at the AI/ML for Medical Treatment & Diagnosis workshop at 911 BaseKX and online, focusing on AI and machine learning in imaging, pharmaceutics, bioinformatics and innovations.
Image 3:Engaging panel discussionto explorepractical, technical, and ethical challenges in AI/ML healthcare applications.
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