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1. Handling-Missing-Modalities-in-Multimodal-Survival-Prediction-for-Non-Small-Cell-Lung-Cancer Handling-Missing-Modalities-in-Multimodal-Survival-Prediction-for-Non-Small-Cell-Lung-Cancer Public

   A missing-aware multimodal framework that fuses CT, Whole-Slide Histopathology, and clinical tabular data for survival prediction in unresectable stage II–III Non-Small Cell Lung Cancer (NSCLC) — w…

   Python 1 1

2. PEFT_Prognosis PEFT_Prognosis Public

   The first systematic benchmark of fine-tuning strategies applied to CNNs and Foundation Models for COVID-19 prognosis prediction from chest X-rays, under realistic clinical constraints of data scar…

   Python 1

3. Multi-Dataset-Multi-Task-Learning-for-COVID-19-Prognosis Multi-Dataset-Multi-Task-Learning-for-COVID-19-Prognosis Public

   A novel Multi-Dataset Multi-Task (MDMT) learning framework that predicts COVID-19 prognostic outcomes from chest X-rays by jointly training on two publicly available datasets with distinct but corr…

   Python 1

4. CheXInstruct-MedGemma-Foundation-Finetuning-Framework CheXInstruct-MedGemma-Foundation-Finetuning-Framework Public

   Forked from cosbidev/CheXInstruct-MedGemma-Foundation-Finetuning-Framework

   A sick project for sick people

   Python

5. GPU-efficiency-course-for-Deep-Learning-frameworks GPU-efficiency-course-for-Deep-Learning-frameworks Public template

   Shell 6

6. Intermediate-Multimodal-Fusion-Bio Intermediate-Multimodal-Fusion-Bio Public

   Forked from cosbidev/Intermediate-Multimodal-Fusion-Bio

   A Systematic Review of Intermediate Fusion in Multimodal Deep Learning for Biomedical Applications.