A Contrastive Variational AutoEncoder for NSCLC Survival Prediction with Missing Modalities | ScienceToStartup | ScienceToStartup

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References (36)

[1]

Accelerating Data Processing and Benchmarking of AI Models for Pathology

2025Andrew Zhang, Guillaume Jaume et al.

[2]

Vision Foundation Models for Computed Tomography

2025Suraj Pai, Ibrahim Hadzic et al.

[3]

Prediction of checkpoint inhibitor immunotherapy efficacy for cancer using routine blood tests and clinical data

Founder's Pitch

"Develop a robust predictive tool for NSCLC survival outcomes using a Multimodal Contrastive Variational AutoEncoder that handles missing clinical data modalities."

Medical AI•Score: 5•View PDF ↗

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A Contrastive Variational AutoEncoder for NSCLC Survival Prediction with Missing Modalities

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References (36)

Founder's Pitch

"Develop a robust predictive tool for NSCLC survival outcomes using a Multimodal Contrastive Variational AutoEncoder that handles missing clinical data modalities."

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A Contrastive Variational AutoEncoder for NSCLC Survival Prediction with Missing Modalities

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Build This Paper

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References (36)

Founder's Pitch

"Develop a robust predictive tool for NSCLC survival outcomes using a Multimodal Contrastive Variational AutoEncoder that handles missing clinical data modalities."

Commercial Viability Breakdown

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