What a great start to the health.tech conference!
At our panel about the AI Revolution in #Healthcare, the room was filled to capacity as PD Dr. med. Dominik Pförringer introduced the panelists on stage.
Here our insights:
PD Dr. med. Kilian Schiller shared findings from our Healthcare Lab pipeline, revealing that 57% of our #startups are already utilizing AI, with an additional 49% considering AI integration into their solutions.
The study indicated that 37% of AI-based technologies in the patient journey are employed at the diagnosis stage, while 44% are used in the treatment sector. Although #AI has not yet reached a stage where it can be solely relied upon by doctors, it currently serves as a valuable tool to enhance efficiency and effectiveness in healthcare processes.
Christoph D. Spinner: In the hospital environment, numerous use cases for AI adoption exist, including navigation for brain surgery, imaging and radiology diagnosis, LLMs for medical search and knowledge bases - with multiple barriers:
Each hospital operates its own IT department, reinventing the wheel instead of utilizing a unified platform to break down silos and prioritize care delivery. There is a need for a more decentralized data platform that encompasses the entire patient journey, allowing doctors and medical teams to focus on disease prevention before patients require hospital care.
Despite Germany allocating 11.2% of its GDP to healthcare, the nation's digital maturity remains low.
𝗧𝗮𝗹𝗸𝗶𝗻𝗴 𝗮𝗯𝗼𝘂𝘁 𝘀𝗼𝗹𝘂𝘁𝗶𝗼𝗻𝘀:
Tamara Gerbert from Brightmind.AI highlighted the latest advancements in AI for MedTech. Including enhancing human-machine interaction for robotic procedures, generative AI-based knowledge management, and autonomous actions, such as Johns Hopkins' Smart Tissue Autonomous Robot outperforming surgeons in bowel anastomosis.
Additionally, multi-model monitoring for humans demonstrates AI's capability to address challenges like big data management, interpreting complex biological data, making unconventional associations, and enabling patient self-diagnosis.
Similarly, Brightmind.AI has developed a platform technology for non-invasive, personalized, at-home brain stimulation to predict migraine attacks. This technology has proven to reduce migraines by 50% and provide relief to up to 90% of migraine sufferers.
Jonas Ils from RYVER.AI highlighted the critical need for access to medical data, often hindered by privacy restrictions and outdated IT systems, particularly for rare cases and underserved patient groups.
Recognizing the importance of this data for training AI to support medical decision-making, RYVER.AI, in partnership with clinical collaborators, is developing privacy-secure synthetic data that accurately mirrors real-world scenarios. This synthetic data is being shared to drive AI innovation, enhance AI reliability, expedite development timelines by months, and reduce data preparation costs by over 80%.
#HT24