Nvidia's AI ambitions in Healthcare are becoming clear

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Welcome to this week’s edition of Supermedic, where we explore the latest developments in artificial intelligence and its transformative impact on healthcare.

Let’s get into it!

Victor

TODAY’S MENU

• Nvidia’s AI Ambitions in Healthcare Are Becoming Clear

• AI Predicts Coronary Artery Disease from Facial Thermal Imaging

• How Autonomous Ultrasound Can Simplify Medical Practice

• Dreaming the Future: Neurons Predict Events in Sleep

• ChatGPT: A Surprising Ally for Autistic Workers

Read time: under 7 minutes

FOCUS OF THE WEEK

Nvidia’s AI Ambitions in Healthcare Are Becoming Clear

Nvidia has quickly become one of the biggest names in AI, and its influence in healthcare is unprecedented. This week, the company’s stock price has been through the roof, even overtaking Apple in terms of market cap.

Originally a pioneer in graphic cards and AI chips, Nvidia now represents 70% of AI semiconductor sales worldwide. Since the AI boom, Nvidia has diversified its activities and envisions a set of solutions that use its hardware technology for various fields, including healthcare. In a short presentation video (above), they showcase some ongoing applications of their solutions across the medical field.

How Nvidia is Changing Healthcare?

During the 2024 GTC AI conference (Nvidia’s annual keynote), the company launched over 20 new AI-powered, healthcare-focused tools, highlighting just how significant medicine is to Nvidia’s future revenue opportunities outside of the tech sector.

They also announced deals with Johnson & Johnson and GE Healthcare. The collaboration with Johnson & Johnson aims to enhance surgical procedures using AI, while the partnership with GE Healthcare focuses on improving medical imaging.

Nvidia also wants to supercharge drug discovery and make diagnoses more accurate. The NVIDIA Clara platform and BioNeMo generative AI service are some examples of their AI-driven tools developed to tackle biomedical challenges.

Let’s have a quick look at Nvidia’s healthcare solutions:

Drug Discovery💊: Nvidia's AI help pharmaceutical companies search molecule databases, generate new molecules, and understand proteins, DNA, and RNA, making drug discovery faster and cheaper.

Their solutions: Nvidia BioNeMo, Nvidia Clara

Genomics 🧬: Nvidia's AI and GPUs enhance the entire genomics workflow, making DNA sequencing more affordable and accurate by speeding up data analysis and improving instrument throughput.

Their solutions: Nvidia Parabricks, Nvidia Clara

Medical Devices 🩺: Nvidia’s AI enhances medical devices, aiding in anomaly detection, improving surgical skills, and optimizing workflows with their full-stack platform

Their solutions: Nvidia Holoscan, Nvidia Clara, Nvidia GPUs

Medical Imaging ☢: Nvidia’s AI in medical imaging enables early detection, medical classification, and automated 3D segmentation, streamlining workflows and connecting multi-modal patient information for better disease understanding.

Thier solutions: Nvidia Monai, Nvidia Clara, Nvidia GPUs

Kimberly Powell, VP of Healthcare at Nvidia, emphasized that AI is already transforming pharmaceutical research, patient diagnostics, and post-operative care. AI integration in healthcare is not just about better outcomes but also about reducing operational costs and increasing efficiency.

Nvidia demonstrates that adopting AI in healthcare is more than just an empty tech trend; it brings tangible benefits. And we are only beginning to scratch the surface…

Source: Nvidia, CNCC, Invezz

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CARDIOLOGY

AI Predicts Coronary Artery Disease from Facial Thermal Imaging

Researchers have developed a new approach to detect coronary artery disease using facial thermal imaging and AI. This non-invasive, real-time method has shown promising results in accurately predicting the presence of the disease.

How it works?

The study, published in BMJ Health & Care Informatics, involved 460 participants with suspected heart disease. Thermal images of their faces were captured and analyzed using AI to develop a predictive model. The results showed that this approach was 13% more effective than traditional pre-test risk assessments.

Key findings:

• The most influential predictive thermal indicators were the overall left-right temperature difference of the face, maximal facial temperature, and average facial temperature.

• The average temperature of the left jaw region was the strongest predictive feature.

• The approach effectively identified traditional risk factors for coronary artery disease, such as high cholesterol, male sex, smoking, and excess weight.

This innovative approach holds great potential for streamlining clinical workflows, enabling instant disease assessment at the point of care, and facilitating mass prescreening.

RESEARCH

How Autonomous Ultrasound Can Simplify Medical Practice

Imagine a world where routine ultrasound exams are performed by intelligent robotic systems, freeing up doctors to focus on patient care and counseling. That's the vision of Prof. Nassir Navab from the Technical University of Munich (TUM).

Key takeaways:

• Autonomous robotic ultrasound systems can perform routine exams without a doctor present, providing 3D images and detecting anomalies.

• In the operating room, these systems offer shared control, assisting surgeons while allowing them to work hands-free when needed.

• Benefits include standardized 3D imaging, comparable data over time, and the potential for remote health scans without medical experts.

Building trust with patients

To build trust between patients and the robotic system, Prof. Navab's team is developing a human-machine interaction that includes clear animations explaining the examination process and simple, non-critical interactions like a symbolic high five.

As people become increasingly comfortable with digital health applications, Prof. Navab believes they will readily accept this innovative technology. Autonomous robotic ultrasound systems could revolutionize routine medical exams, making healthcare more efficient and accessible.

NEUROSCIENCE

The Sleeping Brain May Predict Future Experiences 🔮

Exciting new research from Rice University and the University of Michigan has uncovered that during sleep, some neurons not only replay recent experiences but also anticipate future events.

Researchers monitored neurons in rats as they navigated a maze, then tracked these neurons' activity during sleep. They found that while most neurons maintain stable spatial representations, some undergo changes that prepare the brain for future experiences.

In other words, when the rats revisited the maze, their brains had already done a bit of "pre-work" during naptime.

This study marks a significant advancement in understanding how our brains rewire and form new connections during sleep, challenging the notion that sleep is solely for memory consolidation.

CHATBOT

ChatGPT: A Surprising Ally for Autistic Workers

Researchers at Carnegie Mellon University have explored how individuals with autism interact with AI chatbots like ChatGPT for workplace advice and support. The study found that many autistic adults are already turning to these tools for guidance on social situations, such as making friends at work.

While participants appreciated the quick, easy-to-digest answers provided by the chatbot, some of the advice was found to be questionable or unhelpful. The autism community remains divided on whether using chatbots for this purpose is a good idea, with concerns about privileging neurotypical perspectives over the needs and preferences of autistic individuals.

The researchers emphasize the importance of including the perspectives of people with autism in the development of assistive technologies. Ongoing projects aim to use AI to analyze conversations and provide support for better understanding between autistic and non-autistic individuals in the workplace.

Despite the challenges, AI chatbots show promise as a tool for supporting autistic workers, provided their development is guided by input from the autism community itself.

Other AI Healthcare news :

• Drug Discovery: Machine learning predicts nearly 1 million new antibiotics in the global microbiome.

• Critical Care: Machine learning could personalize oxygenation and improve outcomes for patients on ventilators.

• Psyciatry: New AI algorithm detects rare epileptic seizures by analyzing brain interactions.

• Radiology: AI reduces radiologists' workload and enhances breast cancer screening accuracy and reduces false positives.

• Oncology: AI blood test provides a reliable way to identify lung cancer, study finds.

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