arXiv AI By Ugo Lomoio, Pietro Hiram Guzzi, Pierangelo Veltri

scHFBiMamba: a bidirectional Mamba autoencoder for cardiac disease-state classification from single-nucleus RNA-seq data

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arXiv AI
Oct 16

Imaging-anchored multiomics in cardiovascular disease: integrating cardiac imaging, bulk, single-cell, and spatial transcriptomics

The article reviews how cardiac imaging techniques such as echocardiography, CMR, and CT can be integrated with bulk, single-cell, and spatial transcriptomics to create joint representations that link imaging phenotypes to detailed molecular states. It outlines the representation needs of each modality, compares multimodal fusion strategies, and synthesizes pipelines for radiogenomics, spatial alignment, and image-based gene‑expression prediction, while discussing validation, limitations, and failure modes. The review highlights emerging spatial multiomic maps of human myocardium and atherosclerotic plaque, noting that cost, scalability, and tissue availability remain major barriers to large‑scale cardiovascular translation.

By Minh H. N. Le, Thanh-Huy Nguyen, Tao Li, Bao Quang Gia Le, Han H. Huynh, Monika Raj, Carl Yang, Min Xu, Tuan Vinh, Nguyen Quoc Khanh Le
arXiv Machine Learning
Jun 9

Integrating gene regulatory priors into Transformer attention with scTransformer for interpretable scRNA-seq analysis

arXiv:2606. 09558v1 Announce Type: cross Abstract: Motivation: Transformer-based models are increasingly applied to large-scale single-cell transcriptomics, showing strong performance through self-supervised learning on millions of cells.

By Mikele Milia, Louis Fabrice Tshimanga, Henning Mueller, Manfredo Atzori, Barbara Di Camillo
arXiv AI
Jun 18

Clin-JEPA: A Multi-Phase Co-Training Framework for Joint-Embedding Predictive Pretraining on EHR Patient Trajectories

arXiv:2605. 10840v3 Announce Type: replace-cross Abstract: We present Clin-JEPA, a multi-phase co-training framework for joint-embedding predictive (JEPA) pretraining on EHR patient trajectories.

By Yixuan Yang, Mehak Arora, Ryan Zhang, Baraa Abed, Junseob Kim, Tilendra Choudhary, Md Hassanuzzaman, Kevin Zhu, Ayman Ali, Chengkun Yang, Alasdair Edward Gent, Victor Moas, Rishikesan Kamaleswaran