activity
20172025
most citedIntegrated multimodal artificial intelligence framework for healthcare applications

367 citations · 380 across the 5 of their papers we have counts for

collaborators

5 papers

cs.HC2025

Explainable AI as a Double-Edged Sword in Dermatology: The Impact on Clinicians versus The Public

Xuhai Xu, Haoyu Hu, Haoran Zhang +21

Artificial intelligence (AI) is increasingly permeating healthcare, from physician assistants to consumer applications. Since AI algorithm's opacity challenges human interaction, e…

cs.LG2022★ 6 cited

TabText: Language-Based Representations of Tabular Health Data for Predictive Modelling

Kimberly Villalobos Carballo, Liangyuan Na, Yu Ma +4

Tabular medical records remain the most readily available data format for applying machine learning in healthcare. However, traditional data preprocessing ignores valuable contextu…

cs.LG2022★ 367 cited

Integrated multimodal artificial intelligence framework for healthcare applications

Luis R. Soenksen, Yu Ma, Cynthia Zeng +7

Artificial intelligence (AI) systems hold great promise to improve healthcare over the next decades. Specifically, AI systems leveraging multiple data sources and input modalities…

cs.CV2021★ 7 cited

Evaluating Deep Neural Networks Trained on Clinical Images in Dermatology with the Fitzpatrick 17k Dataset

Matthew Groh, Caleb Harris, Luis Soenksen +5

How does the accuracy of deep neural network models trained to classify clinical images of skin conditions vary across skin color? While recent studies demonstrate computer vision…

cs.CV2017

A semi-automated segmentation method for detection of pulmonary embolism in True-FISP MRI sequences

Luis R Soenksen, Luis Jiménez-Angeles, Gabriela Melendez +1

Pulmonary embolism (PE) is a highly mortal disease, currently assessed by pulmonary CT angiography. True-FISP MRI has emerged as an innocuous alternative that does not hold many of…