Hear about the evaluation and clinical implementation of artificial intelligence tools in #neurology from Kolachalama laboratory of Boston U Chobanian & Avedisian School of Medicine: 🎥 ow.ly/Cypr50VJyWZ #AANAM #NeuroTwitter @AANMember

Who would have thought podcasts could train a smarter AI? 🎧🤖 Meet PodGPT (podgpt.org), an open-source LLM powered by thousands of expert STEMM conversations. It boosts accuracy, understands complex topics, and speaks multiple languages. A new era for research &

Is anyone attending #ICML2025 this year? If so, please stop by our poster: “Active feature acquisition via explainability-driven ranking”, which will be presented by my PhD student Osman Berke Guney (@bu_ece). The session will be held on Tuesday, July 15, 2–4:30pm EDT, East Exhibition

📢 Exciting News: Kolachalama laboratory’s latest work is published in Nature Communications!! Their team has developed an AI model that predicts Alzheimer's disease biomarkers (Aβ and τ) using widely available clinical data. nature.com/articles/s4146….

A new AI tool designed by researchers at Boston University helps to accurately predict biomarkers of Alzheimer’s disease. To learn more, click here: bit.ly/4mfrUpK

A nice video summary of our paper entitled "Development and validation of an interpretable deep learning framework for Alzheimer’s disease classification", published in Brain (2020). youtu.be/quwlODDgtgQ Source: NotebookLM

AI-driven fusion of multimodal data for Alzheimer’s disease biomarker assessment nature.com/articles/s4146… #BDF10years

The Kolachama Lab is tackling the PET scan bottleneck in Alzheimer’s diagnosis with an AI model that predicts amyloid-β & tau status from 12,185 patients across 7 cohorts, offering a scalable alternative for pre-screening & guiding PET imaging. nature.com/articles/s4146…

Our new paper in Human Brain Mapping (@WileyNeuro) presents an anatomy-guided, modality-agnostic framework to assess disease-related abnormalities in brain MRI. Please check it out! doi.org/10.1002/hbm.70… Boston U Chobanian & Avedisian School of Medicine BU Computer Science BU Computing & Data Sciences (CDS)

Pleased to share our perspective article entitled "An AI‐first framework for multimodal data in Alzheimer's disease and related dementias" - Alzheimer's & Dementia - alz-journals.onlinelibrary.wiley.com/doi/10.1002/al… @WileyNeuro Alzheimer's & Dementia Journals ISTAART

#MachineLearning identifies compounds that could rejuvenate aging brain cells, offering hope for neurodegenerative disease treatment: hubs.la/Q03N_rYT0 #NeuroTwitter @AANMember Antonio del Sol's Lab Kolachalama laboratory Boston University Mount Sinai Neurology

Here is our new work on detecting TDP-43 pathology in spinal fluid, a key unmet need for patients with neurodegenerative disease. We are looking to hire a postdoc to further develop and test our assays - please retweet! medrxiv.org/content/10.110…

#MachineLearning identifies compounds that could rejuvenate aging brain cells, offering hope for neurodegenerative disease treatment: hubs.la/Q03PLN3L0 #NeuroTwitter @AANMember Antonio del Sol's Lab Kolachalama laboratory Boston University Mount Sinai Neurology

Excited to share our new perspective on how digital tech advances are revolutionizing early #Alzheimers detection, enabling precision brain health & global open science! 🧠📷doi.org/10.1002/alz.70… #ADRD Alzheimer's & Dementia Journals ISTAART

A new paper by Varuna Jasodanand, BU Graduate Medical Sciences PhD student in the Kolachalama laboratory (Kolachalama laboratory), explores the use of AI-driven fusion in multimodal data for Alzheimer’s disease biomarker assessment: bit.ly/4qP2HVA. Published Nature Communications

It was great to present our latest work on multimodal AI at the JH AITC Conference on Large Language Models and Large Foundational Models on 11/20/25. Thanks to JHU AI/Tech & Aging, Johns Hopkins University Bloomberg Center, and Johns Hopkins Data Science and AI Institute for organizing the event. -- nature.com/articles/s4146… --