🚨 Pulse of Innovation 🚨

Breaking news in the healthcare AI

Healthcare 2.0: See the Future of Medicine Through Apple's Eyes?

• Apple Vision Pro is making waves in healthcare with its groundbreaking uses, such as Cedars-Sinai's Xaia for immersive mental wellness therapy and Boston Children’s Hospital's CyranoHealth app for stress-free medical training. However, challenges still need to be addressed, including the need for rigorous planning, training for healthcare professionals, and addressing security and privacy concerns related to sensitive patient data.

• This mixed reality technology promises to transform telemedicine, surgical planning, and medical education by providing more interactive and holistic healthcare experiences. However, factors such as high cost, adoption pace, and physical impact on users highlight the need to balance the technology's innovative potential and the practical considerations of integrating it into everyday healthcare practices.

Super Bowl AI: AI in NFL for player safety (this is #ourlane)

• NFL players were equipped with RFID technology, resulting in the collection of over 500 million data points. These data points included video data capturing players' movements, covering a distance of over 15,000 miles. The collected data was then utilized in a machine-learning model to better understand player movements and identify positions more susceptible to injuries.

• A notable outcome of this application was the introduction of the NFL's new fair catch rule for kickoffs in 2023. Under this rule, kick returners can now call for a fair catch even if the ball is kicked short of the end zone, effectively ending the kick return play. This rule change is anticipated to lead to a 7% reduction in kickoff returns and a consequent decrease of 15% in concussion injuries.

🧑🏼‍🔬 Bench to Bedside👨🏽‍🔬

Developments in healthcare AI research and innovations

AI chatbot could reduce the accessibility gap in mental health services

• The UK's National Health Services (NHS) implemented a personalized AI chatbot for self-referral to mental health services. The results showed a 15% increase in referrals with the personalized chatbot, compared to a 6% increase with traditional self-referral methods like web forms.

• Notably, the AI chatbot saw even greater increases in self-referrals from minority groups, such as non-binary individuals (179%), Blacks (40%), and Asians (39%). This highlights the potential of the chatbot as a valuable tool for addressing the accessibility gap in mental health care for minority populations.

AI-powered cancer screening system wins FDA approval

• The Hologic digital cytology system–a diagnostic tool that examines cells under a microscope to detect abnormalities or diseases–integrates deep learning-based AI with advanced volumetric imaging technology to aid in detecting precancerous lesions and cervical cancer cells.

• Given the FDA approval, this system is already available in Europe, Australia, and New Zealand and is expected to be available in the USA later this year. It could reduce false negatives by 28% while allowing physicians to do remote case reviews.

• The system is scalable to meet evolving lab needs with digital image processing resources/infrastructure for faster case reviews.

🩺 Start-Up Stethoscope 💵 

Trending startups and technologies impacting clinical practice

The AI Doc Whisperer: Revolutionizing Clinical Documentation with a $70M Boost

• Ambience Healthcare has secured $70 million in funding for their AI platform designed to reduce clinician burnout by aiding with documentation, coding, referrals, and after-visit summaries. This enhances efficiency and shifts the focus towards patient care.

• The platform stands out for its specialized fine-tuning, allowing seamless integration with major EHR systems. It offers comprehensive tools that streamline administrative tasks, improving clinician satisfaction and increasing patient engagement.

AiCure raises $16 million dollars to enhance AI driven clinical trials business

• The AiCure is an AI-driven clinical trial platform with patient connect that allows real-time monitoring and dosage adjustments, as well as AiCure platform long-term data storage and remote monitoring and visualization of data for sponsors to track the progress of the trials.

• The company has also recently secured seven additional patents in the US market and launched clinical site services that provide AI-driven customized clinical trial data management solutions for participating sites to reduce the burden on on-site personnel.

🤖Patients First, AI Second🤖

Ethical and regulatory landscape of healthcare AI

Is 2024 the year for AI Regulations?

• The year 2024 is poised for significant advancements in AI regulation globally, focusing on enhancing accountability and transparency among tech companies. Efforts will include enacting the first comprehensive AI laws and frameworks for sector-specific regulation, particularly in the EU and the US, emphasizing industry-friendly policies and risk-based regulatory approaches.

• Europe leads with the AI Act, setting stringent standards for high-risk AI applications in sectors like healthcare and policing, aiming for quick implementation. Meanwhile, the US gears up for a nuanced regulatory landscape shaped by President Biden's executive order, focusing on transparency and sector-specific rules.

👩‍⚕️AI in the Clinic 🏥

Real-world and practical use of healthcare AI in clinic

AI use in Retinal disease management is moving into the Clinic

• AI technology is revolutionizing retina care, providing greater precision in diagnosis and treatment. RetInSight's Fluid Monitor and GA Monitor use AI to monitor disease progression and fluid analysis in patients with neovascular age-related macular degeneration (AMD), gaining approval for clinical use in Europe.

• Automated patient identification for clinical trials with AI algorithms developed by centers like the Wisconsin Reading Center is transforming diabetic retinopathy screening. AI-powered OCT analysis can enhance early detection and management of retinal diseases, streamlining clinical workflows and benefiting patients, physicians, and healthcare systems alike.

AI automated triage system reduces radiology reporting times.

• SimonMed, an independent radiology practice operating in over 10 states and consisting of more than 200 board-certified radiologists, has successfully implemented AI triage automation in its reporting process. With this technology, the AI system identifies abnormalities such as fractures and prioritizes the corresponding patient images to be reviewed by a radiologist within 10 minutes of the AI report.

• A qualitative study was conducted across 14 centers involving 1442 patients to evaluate the effectiveness of their triage AI automated reporting. The results demonstrated an impressive 82% reduction in reporting times and a sensitivity rate of 96%-100% for bone abnormality reporting.