BrainX Waves: The Newsletter of BrainX Community
Piyush Mathur MD,FCCM,FASA,FAMIA
Anesthesiologist,Intensivist, AI researcher, Innovator, Quality Professional, Educator, Author, at the Cleveland Clinic with more than 20 year clinical experience.All views and opinions expressed are mine.
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Voices of Innovation – AI: Fulfilling the Promise of AI in Healthcare
Edited By Edward Marx , Sakshika D. , Frank A. Papay MD , Piyush Mathur MD,FCCM,FASA,FAMIA
As an industry, we have clearly made great technological advancements, and yet we find ourselves behind peer industries when it comes to innovation with patient care, customer experience, augmented intelligence, virtual care, and cybersecurity. One reason for the lack of innovation velocity is the need for a universally adopted model or best practice framework. The time has come for Voices of Innovation – AI. Artificial intelligence is what some call the fourth transformative revolution in human history. Healthcare is among the many industries with significant opportunities for the use of AI and machine learning, as the convergence of technology and healthcare will result in significant innovation. This book is both practical and inspirational. Using the HIMSS model for innovation as the structural framework, Voices of Innovation – AI will showcase the great AI innovations being implemented across healthcare globally.
With contributions from leading authorities in this field, this book will become the de facto resource for any organization seeking to leverage AI effectively. Loaded with numerous case studies and stories of successful innovation projects, this book helps the reader understand how to leverage AI to help fulfill the promise of technology in enabling superior business and clinical outcomes.
Connect
At the BrainX Community Live! May 2025 event on the real-world application of Generative AI in clinical practice, Prof. Kee Yuan Ngiam , National University Hospital, Singapore, shared his experiences with the implementation of AI in clinical practice in a talk titled, “Implementing AI in Clinical Practice”. Watch his presentation, which detailed building an infrastructure to support the implementation of AI in a health system, real-world use cases in current deployment and how LLMs are being integrated to support clinicians.
Related publication: Integration of customised LLM for discharge summary generation in real-world clinical settings: a pilot study on RUSSELL GPT
Datasets
Bridge2AI-Voice: Voice dataset linked to health information
Bridge2AI-Voice v2.0 contains data for 19,271 recordings collected from 442 participants across five sites in North America. Participants were selected based on known conditions which manifest within the voice waveform including voice disorders, neurological disorders, mood disorders, and respiratory disorders.
The BRIDGE-Open dataset is an open-access subset of the datasets used by the BRIDGE benchmark. This dataset includes the 55 tasks of the open-access datasets that can be released to the public. Due to privacy and security considerations of clinical data, regulated-access datasets can not be directly published. However, all detailed task descriptions and their corresponding data sources are available in the BRIDGE paper, Supplementary Section 5. Importantly, all 87 datasets have been verified to be either fully open-access or publicly accessible via reasonable request in the systematic review.
OpenPOCUS (Lung ultrasound images)
The largest annotated lung ultrasound (LUS) repositories to date—over 300,000 de-identified frames, drawn from 226 patients with diverse respiratory diagnoses. Includes both COVID and non-COVID pneumonia, pulmonary edema, COPD, healthy controls, and more.
This dataset consists of 4571 patients (rows) with 73 features (columns). It includes extensive demographics, past history, extensive lab work, activity levels, light levels, cog scores, and many more variables. The final column is diabetes (0, 1) that could be used in a classification model.
This file contains the dataset. It has 24 diseases each with 50 symptoms giving a total of 1200 data points.
Conferences
Additional BXC-featured publications
Critical Care/ General/ Generative AI/ LLM
Development and prospective implementation of a large language model based system for early sepsis prediction Supreeth P. Shashikumar, Sina Mohammadi, Rishivardhan Krishnamoorthy, Avi Patel, Gabriel Wardi, Joseph C. Ahn, Karandeep Singh , Eliah Aronoff-Spencer & Shamim Nemati
General/ Generative AI/ LLM
BRIDGE: Benchmarking Large Language Models for Understanding Real-world Clinical Practice Text Jiageng Wu, Bowen Gu, et al.
General/ Generative AI/ LLM
A framework to assess clinical safety and hallucination rates of LLMs for medical text summarisation (CREOLA) Elham Asgari, Nina Montaña-Brown, Magda Dubois, Saleh Khalil, Jasmine Balloch, Joshua Au Yeung & Dominic Pimenta
General/ Generative AI/ LLM
Physician- and Large Language Model–Generated Hospital Discharge Summaries
Christopher Y. K. Williams, Charumathi Raghu Subramanian, MD , Syed Salman Ali, et al.
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Frank A. Papay MD Jacek B. Cywinski, M.D.,FASA Ashish K. Khanna MD,MS,FCCP,FCCM,FASA Kamal Maheshwari MD MPH FASA Chintan Dave, MD Raghav Awasthi Shreya Mishra Julia Maslinski Rachel Grasfield Hajra Arshad Edward Marx Sai Prasad Ramachandran Suyash Khubchandani Vidur Mahajan, MD, MBA Rahul Kashyap, MBBS, MBA, FCCM Chaitanya Mamillapalli, MD, MRCP, FAPCR, FACE Sandeep Reddy Dwarikanath Mahapatra Asma Alshukaili Anurag Nimonkar Aarit Atreja Ashish Atreja, MD, MPH Berk B. Ozmen, M.D. Graham Schwarz Sharan Jhaveri △🦦🎙️ Yanshan Wang, PhD, FAMIA Reem Khatib Moises Auron, MD, FAAP, FACP, SFHM, FRCP(Lon), FRCPCH Avirup Guha, MD, MPH, RPVI, FICOS, FACC, FAHA JAI NAHAR, MD MBA Animesh Tandon, MD, MS Anthony Chang, MD, MBA, MPH, MS Teresa Rincon Shalini Shree Murari Mandal Sameer Shaikh Natalia Hakimzadeh Nishant Singh Atharva Bhattad Lovish Kundu