most citedMeDSLIP: Medical Dual-Stream Language-Image Pre-training with Pathology-Anatomy Semantic Alignment

2 citations · 2 across the 4 of their papers we have counts for

collaborators

5 papers

eess.SP2025

Multimodal Latent Fusion of ECG Leads for Early Assessment of Pulmonary Hypertension

Mohammod N. I. Suvon, Shuo Zhou, Prasun C. Tripathi +7

Recent advancements in early assessment of pulmonary hypertension (PH) primarily focus on applying machine learning methods to centralized diagnostic modalities, such as 12-lead el…

eess.IV2024

TabMixer: Noninvasive Estimation of the Mean Pulmonary Artery Pressure via Imaging and Tabular Data Mixing

Michal K. Grzeszczyk, Przemysław Korzeniowski, Samer Alabed +3

Right Heart Catheterization is a gold standard procedure for diagnosing Pulmonary Hypertension by measuring mean Pulmonary Artery Pressure (mPAP). It is invasive, costly, time-cons…

cs.CV2024

Interpretable Multimodal Learning for Cardiovascular Hemodynamics Assessment

Prasun C Tripathi, Sina Tabakhi, Mohammod N I Suvon +5

Pulmonary Arterial Wedge Pressure (PAWP) is an essential cardiovascular hemodynamics marker to detect heart failure. In clinical practice, Right Heart Catheterization is considered…

cs.LG2024

Multimodal Variational Autoencoder for Low-cost Cardiac Hemodynamics Instability Detection

Mohammod N. I. Suvon, Prasun C. Tripathi, Wenrui Fan +7

Recent advancements in non-invasive detection of cardiac hemodynamic instability (CHDI) primarily focus on applying machine learning techniques to a single data modality, e.g. card…

cs.CV2024★ 2 cited

MeDSLIP: Medical Dual-Stream Language-Image Pre-training with Pathology-Anatomy Semantic Alignment

Wenrui Fan, Mohammod N. I. Suvon, Shuo Zhou +6

Pathology and anatomy are two essential groups of semantics in medical data. Pathology describes what the diseases are, while anatomy explains where the diseases occur. They descri…