BrainX Waves: The Newsletter of BrainX Community

July 2025: Issue 13

Jul 30, 2025

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AI and Robotics ready to transform perioperative patient care

During a trip to China, Co-founder and CEO of Nvidia Jensen Huang was asked by a journalist: “If you are a 22-year-old version of Jensen [who] just graduated today in 2025 but with the same ambition, what would you focus on?”

To that, the Nvidia CEO said: “For the young, 20-year-old Jensen, that’s graduated now, he probably would have chosen ... more of the physical sciences than the software sciences,” adding that he actually graduated two years early from college, at age 20.

Applications of physical reasoning include predicting outcomes, such as where a ball will roll, understanding how much force is needed to grip an object without damaging it and inferring the presence of a pedestrian behind a car.

“And when you take that physical AI and then you put it into a physical object called a robot, you get robotics,” he added. “This is really, really important for us now, because we’re building plants and factories all over the United States.”

Ref: https://www.cnbc.com/2025/07/18/nvidia-ceo-jensen-huang-study-field-computer-science-software-gpu-alexnet-generative-physical-ai-university.html

Extending the same argument, we are now seeing combined applications of deep learning and robotics come to the operating rooms.

In a recently published study, a Robotic Flexible Intubation System (RFIS) which uses Convolutional Neural Network(CNN) was trialed for airway intubation on a simulation manikin.

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Register today to join us on August 19, 2025 at 11 am – Noon ET/8:30-9:30 PM India time via Zoom. This session is themed: “Radiology platforms for AI implementation”, features Drs. Pranav Rajpurkar, Co-founder of a2z Radiology AI, and Vidur Mahajan, CEO for CARPL.ai

https://us02web.zoom.us/meeting/register/Un6VwGWsQXyvo048unjyVA#/registration

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Datasets (Open source)

Mediflow: Synthetic clinical dataset

A large-scale synthetic instruction dataset of 2.5M rows (~700k unique instructions) for clinical natural language processing covering 14 task types and 98 fine-grained input clinical documents

PadChest-GR (Grounded-Reporting)

A public bilingual dataset of 4,555 CXR studies with substantiated reports (3,099 abnormal and 1,456 normal), each containing complete lists of sentences describing individual positive and negative findings in English and Spanish. In total, PadChest-GR contains 7,037 sentences of positive findings and 3,422 sentences of negative findings. This dataset is derived from the PadChest dataset.

More Data