10 citations · 26 across the 6 of their papers we have counts for
6 papers
Granite Vision: a lightweight, open-source multimodal model for enterprise Intelligence
Granite Vision Team, Leonid Karlinsky, Assaf Arbelle +60
We introduce Granite Vision, a lightweight large language model with vision capabilities, specifically designed to excel in enterprise use cases, particularly in visual document un…
Creation and Validation of a Chest X-Ray Dataset with Eye-tracking and Report Dictation for AI Development
Alexandros Karargyris, Satyananda Kashyap, Ismini Lourentzou +8
We developed a rich dataset of Chest X-Ray (CXR) images to assist investigators in artificial intelligence. The data were collected using an eye tracking system while a radiologist…
Automatic Diagnosis of Pulmonary Embolism Using an Attention-guided Framework: A Large-scale Study
Luyao Shi, Deepta Rajan, Shafiq Abedin +3
Pulmonary Embolism (PE) is a life-threatening disorder associated with high mortality and morbidity. Prompt diagnosis and immediate initiation of therapeutic action is important. W…
Pi-PE: A Pipeline for Pulmonary Embolism Detection using Sparsely Annotated 3D CT Images
Deepta Rajan, David Beymer, Shafiqul Abedin +1
Pulmonary embolisms (PE) are known to be one of the leading causes for cardiac-related mortality. Due to inherent variabilities in how PE manifests and the cumbersome nature of man…
Generalization Studies of Neural Network Models for Cardiac Disease Detection Using Limited Channel ECG
Deepta Rajan, David Beymer, Girish Narayan
Acceleration of machine learning research in healthcare is challenged by lack of large annotated and balanced datasets. Furthermore, dealing with measurement inaccuracies and explo…
Disease Detection in Weakly Annotated Volumetric Medical Images using a Convolutional LSTM Network
Nathaniel Braman, David Beymer, Ehsan Dehghan
We explore a solution for learning disease signatures from weakly, yet easily obtainable, annotated volumetric medical imaging data by analyzing 3D volumes as a sequence of 2D imag…