T2. In this commentary in The Lancet Digital Health, we use an #AI in medicine/autonomous car analogy, to develop a corollary to DoT definitions of levels of AI autonomy with consideration of liability based on risk. Danielle Bitterman, MD Hugo Aerts #RadAIchat thelancet.com/journals/landi…

Congratulations to #HROP rising 🌟 Tafadzwa L. Chaunzwa for receiving this year's Radiation Oncology Institute-The ASTRO Foundation #AI in #radonc research award. Dr. Chaunzwa will be investigating predictive #radiomics biomarkers in NSCLC patients at Brigham and Women’s Radiation Oncology Dana-Farber with mentors Ray Mak, MD Hugo Aerts

The collaborative study “Deep learning to predict 10-year cardiovascular risk from chest radiographs.” by Vineet Raghu Michael Lu and coauthors Jakob Weiss Kaavya Paruchuri Pradeep Natarajan Hugo Aerts was featured on cnn morning. Mass General Heart MGH Cardiovascular Research Center Mass General Imaging @MGH_RI

Today our important study on air pollutants in the promotion of lung cancer has been published in nature led by Will Hill Emilia Lim Clare Weeden Swanton Lab ...Thread below🧵nature.com/articles/s4158…

Cachexia is a devastating condition in patients with cancer. Our study on cancer cachexia in #TRACERx is out today in Nature Medicine led by Othman Al-Sawaf, @MariamJHanjani, Swanton Lab: nature.com/articles/s4159… Key results in a brief 🧵

Excited to share our TRACERx nature publication on circulating tumor DNA (#ctDNA, #MRD) detection in resectable lung cancer led by @AbboshChris, @Afrankell, Judit Kisistok, Thomas Harrison, Aaron Garnett, Nicolai Birkbak and Nicholas McGranahan 👇👇👇 Tweetorial🧵 nature.com/articles/s4158…

Is ChatGPT a reliable source for cancer treatment recommendations 🤖? Our study, out now in JAMA Oncology, found that the chatbot included guideline non-concordant recommendations for common cancer diagnoses 1/3 of the time: jamanetwork.com/journals/jamao… #ChatGPT #LLM #NLProc

Please check out our paper for more. ChatGPT output and scores are available at the project github github.com/AIM-Harvard/Ch…. Congrats to Shan Chen and thank you to wonderful coauthors! Mike Foote Benjamin Kann, MD Hugo Aerts Ray Mak, MD AIM @ Harvard CHIP Informatics

Thanks for highlighting the studies - We are still in early days but so much potential. Looking forward to working towards responsible and equitable AI for healthcare as outlined in Atul Butte's wonderful editorial!

1/ Check out this preprint that describes how we developed and validated a new #AI-based biomarker that we are calling “FaceAge”, which uses a simple face #photo to predict outcomes in #cancer patients! medrxiv.org/content/10.110… #oncology #AImedicine #FaceAge

I'm excited to share a groundbreaking approach leveraging foundation models to develop high-performance radiomic biomarkers, even when confronted with limited training data. Check out our work in Nature Machine Intelligence: nature.com/articles/s4225…

Chest x-rays, the most frequently performed imaging test in medicine, have rich embedded information that humans can't see. Here #AI detects 10-year cardiovascular risk as well as the traditional (ASCVD) score! acpjournals.org/doi/10.7326/M2… Karl Jakob Weiss Vineet Raghu @kparuchur

#TransferLearning + self-supervision to characterize glioma doi.org/10.1148/ryai.2… Hugo Aerts Brigham and Women's Hospital Tina Young Poussaint, MD, FACR #NeuroRad #ML #MachineLearning

Cross-Care is our new #LLM benchmark for measuring safety/bias in the #healthcare domain. We find misalignments between real biomedical facts, pretraining data, and LLM knowledge representation. Read more (arxiv.org/abs/2405.05506) and explore our website (crosscare.net)

Did you know your face can reveal your biological age? Mass General Brigham Research has developed FaceAge, an #AI algorithm that predicts biological age survival outcomes for patients with cancer using a single photo. Patients with cancer appeared five years older than their actual age, and

Did you know your face can reveal your biological age? Researchers at Mass General Brigham developed FaceAge, an #AI algorithm that predicts biological age and survival outcomes for patients with cancer using a single photo. Patients with cancer appeared five years older than their