output
20142025
most citedIntegrating Artificial Intelligence with Real-time Intracranial EEG Monitoring to Automate Interictal Identification of Seizure Onset Zones in Focal Epilepsy

102 citations

Showing 2020Show all

7 papers · 1 filter

stat.ME20201 cited

Covariate Adaptive Family-wise Error Rate Control for Genome-Wide Association Studies

Huijuan Zhou, Xianyang Zhang, Jun Chen

The family-wise error rate (FWER) has been widely used in genome-wide association studies. With the increasing availability of functional genomics data, it is possible to increase…

eess.IV20201 cited

Democratizing Artificial Intelligence in Healthcare: A Study of Model Development Across Two Institutions Incorporating Transfer Learning

Vikash Gupta1, Holger Roth, Varun Buch3 +9

The training of deep learning models typically requires extensive data, which are not readily available as large well-curated medical-image datasets for development of artificial i…

q-bio.NC202036 cited

Brain volume: An important determinant of functional outcome after acute ischemic stroke

Markus D. Schirmer, Kathleen L. Donahue, Marco J. Nardin +38

Objective: To determine whether brain volume is associated with functional outcome after acute ischemic stroke (AIS). Methods: We analyzed cross-sectional data of the multi-site, i…

cs.CV20207 cited

Learning Semantics-enriched Representation via Self-discovery, Self-classification, and Self-restoration

Fatemeh Haghighi, Mohammad Reza Hosseinzadeh Taher, Zongwei Zhou +2

Medical images are naturally associated with rich semantics about the human anatomy, reflected in an abundance of recurring anatomical patterns, offering unique potential to foster…

cs.IR20202 cited

A Qualitative Evaluation of Language Models on Automatic Question-Answering for COVID-19

David Oniani, Yanshan Wang

COVID-19 has resulted in an ongoing pandemic and as of 12 June 2020, has caused more than 7.4 million cases and over 418,000 deaths. The highly dynamic and rapidly evolving situati…

cs.LG20203 cited

Augmented Curation of Unstructured Clinical Notes from a Massive EHR System Reveals Specific Phenotypic Signature of Impending COVID-19 Diagnosis

FNU Shweta, Karthik Murugadoss, Samir Awasthi +24

Understanding the temporal dynamics of COVID-19 patient phenotypes is necessary to derive fine-grained resolution of pathophysiology. Here we use state-of-the-art deep neural netwo…