XPANSE, a new, ecosystem-building summit showcasing the potential of integrating science, tech and art attracted thousands of innovators to Abu Dhabi in November.
Industry leaders, scientific researchers, tech pioneers and investors gathered to discuss, among other things, quantum computing, AI, genomics, embodied intelligence, next gen 2D materials, and sentient cities. Unlike most tech conferences, art and playful creativity played an equally starring role – a vision of what the future could look and feel like if wildly differing disciplines blurred the boundaries between art, science and tech.
Abu Dhabi is an apropos backdrop. It’s multi-billion-dollar National Innovation Strategy drives investments across blockchain, fintech, renewable energy and AI, supported by research produced at the government-funded Technology Innovation Institute. A satellite version of The Louvre is the foundation of Abu Dhabi’s vibrant contemporary art scene. The capital city was ranked the fastest-growing emerging ecosystem in the Middle East and North Africa (MENA) this year in the 2024 Global Startup Ecosystem Report. The ranking reflects 28 percent growth based on exits and startup valuations.
But, back to XPANSE, where artists and scientists co-produced interactive installations like a speculative living alphabet generated by a colony of microalgae and artificial neural networks.
In addition to startup pitches, XPANSE provided a platform for early career scientists, PhD students and post-doc fellows to pitch their research, each at various stages of development – some already in use commercially or on a trial basis. These are three of the most compelling Health and MedTech solutions presented.
Vital Rhythms is a deep learning software used for the assessment of heart failure stages using novel multi-parameter images.
Heart failure produces varying metrics in patients at different, and even within the same stages requiring continuous monitoring day and night to get an accurate reading. The current standard is EKG (electrocardiography) which is bulky and used in medical settings, rather than at home. Vital Rhythms uses a personalised, deep learning-based polar image populated with a patient’s clinical information to deliver 24-hour analysis from a device users wear at home. Embedded with AI, Vital Rhythms can distinguish which hours were the most critical in determining the impacts and stages of heart failure and is already being used by patients at home and in hospitals.
iATOSSA is an app that seeks to provide early risk assessment, monitoring and self-management of breast cancer through smartphone-based thermal imaging and advanced AI.
Breast cancer is the most diagnosed cancer globally, with high mortality rates. Yet, early risk prediction and self-management tools are limited. The iATOSSA app integrates deep learning models with features like symptom tracking, medication adherence monitoring, and behavioral data analysis. iATOSSA aims to empower users—both high-risk individuals and survivors—through at-home data collection, intelligent insights, and a user-friendly interface to provide practical support for patients. Oncologists are working with biomedical engineers on the app design and clinical evaluation. The three main goals for the app are: home-based risk assessment accuracy, behavioural disruption and side effect monitoring, along with a bot providing support and personalized self-management guidance.
LaparoSense is a technology designed to overcome the lack of tactile feedback in minimally invasive surgery (MIS), which, despite success rates, limits a surgeon’s sense of touch, impacting outcomes due to lack of precision.
Tactile sensing is an important tool in improving accuracy during MIS in identifying things like tumor location and reducing tissue damage. Think of it like picking fruit and veg. A LaparoSense prototype tested on different samples applying the same force was able to measure thickness of tissue, among other metrics, at different angles. It can also be re-used and implemented with other surgical grasping instruments. Designed with soft, microfluidic sensors in the handle of laparoscopic graspers, LaparoSense improves task completion time by 30 percent, differentiate between tissues and detect hidden lumps inside tissue, as well as identify the location of tumors. LaparoSense founders are in talks with large medical technology companies to scale and take it to market. A non-provisional patent application has been filed.
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