Multi-Modal Biomedical Data Fusion — Hands-on

Build end-to-end pipelines that combine genomics/proteomics/metabolomics with clinical tables, imaging-derived features and biomedical text. Learn data alignment, missing-modality handling, representation learning, and modern fusion architectures to deliver stronger, more generalizable models with clear reporting.

Multi-Modal Biomedical Data Fusion

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Session Index

Session 1 — Modalities, Alignment & Fusion Basics Session 2 — Representation Learning & Contrastive Session 3 — Cross-Modal Transformers & Missingness Session 4 — Mini Capstone: Multi-Modal Pipeline

Session 1

Fee: Rs 14,200

Modalities, Alignment & Fusion Basics

Modalities & schemas

omics clinical EHR imaging/text

Fusion strategies

early/late/intermediate co-training/co-regularization feature vs decision

ID/linkage & temporal alignment

patient keys visit windows sampling sync

Session 2

Fee: Rs 19,600

Representation Learning & Contrastive

Latent spaces & embeddings

autoencoders/VAEs CCA/DeepCCA manifold learning

Contrastive & alignment losses

InfoNCE/Triplet Barlow Twins/SimCLR cross-modal distillation

Toolchain & data loaders

PyTorch/Lightning HuggingFace tf.data

Session 3

Fee: Rs 25,200

Cross-Modal Transformers & Missingness

Architectures for fusion

co-attention late-fusion transformers gated fusion

Handling missing modalities

mixture-of-experts token masking imputation/adapters

Evaluation, robustness & ablations

modality drop tests domain shifts calibration/uncertainty

Session 4

Fee: Rs 31,800

Mini Capstone: Multi-Modal Pipeline

Assemble a fusion model on a real dataset

Theory + Practical

Explainability & reporting

modality attributions counterfactuals model card

Deliverables: code, metrics & PDF brief

notebook/script ablation table calibration plots

PDF

Multi-Modal Biomedical Data Fusion Training | Contrastive Learning, Cross-Modal Transformers, Robust Fusion

Multi-Modal Biomedical Data Fusion — Hands-on