37 citations · 43 across the 7 of their papers we have counts for
7 papers
Exploring the Design Space of 3D MLLMs for CT Report Generation
Mohammed Baharoon, Jun Ma, Congyu Fang +2
Multimodal Large Language Models (MLLMs) have emerged as a promising way to automate Radiology Report Generation (RRG). In this work, we systematically investigate the design space…
ECG-FM: An Open Electrocardiogram Foundation Model
Kaden McKeen, Sameer Masood, Augustin Toma +2
Conventional task-specific electrocardiogram (ECG) analysis models require large annotated datasets to train. Foundation models mitigate this burden by leveraging self-supervised p…
WangLab at MEDIQA-M3G 2024: Multimodal Medical Answer Generation using Large Language Models
Ronald Xie, Steven Palayew, Augustin Toma +2
This paper outlines our submission to the MEDIQA2024 Multilingual and Multimodal Medical Answer Generation (M3G) shared task. We report results for two standalone solutions under t…
WangLab at MEDIQA-CORR 2024: Optimized LLM-based Programs for Medical Error Detection and Correction
Augustin Toma, Ronald Xie, Steven Palayew +2
Medical errors in clinical text pose significant risks to patient safety. The MEDIQA-CORR 2024 shared task focuses on detecting and correcting these errors across three subtasks: i…
GPT-4V(ision) Unsuitable for Clinical Care and Education: A Clinician-Evaluated Assessment
Senthujan Senkaiahliyan, Augustin Toma, Jun Ma +6
OpenAI's large multimodal model, GPT-4V(ision), was recently developed for general image interpretation. However, less is known about its capabilities with medical image interpreta…
WangLab at MEDIQA-Chat 2023: Clinical Note Generation from Doctor-Patient Conversations using Large Language Models
John Giorgi, Augustin Toma, Ronald Xie +4
This paper describes our submission to the MEDIQA-Chat 2023 shared task for automatic clinical note generation from doctor-patient conversations. We report results for two approach…
Clinical Camel: An Open Expert-Level Medical Language Model with Dialogue-Based Knowledge Encoding
Augustin Toma, Patrick R. Lawler, Jimmy Ba +3
We present Clinical Camel, an open large language model (LLM) explicitly tailored for clinical research. Fine-tuned from LLaMA-2 using QLoRA, Clinical Camel achieves state-of-the-a…