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Prognosis

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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/88vikram/pyebm

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Disease Progression Timeline Estimation for Alzheimer's Disease using Discriminative Event Based Modeling

https://github.com/8medom/sigfittest

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A comprehensive comparison of tools for fitting mutational signatures

https://github.com/ABILab-CUHK/VisionFM

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VisionFM: a Multi-Modal Multi-Task Vision Foundation Model for Generalist Ophthalmic Artificial Intelligence

https://github.com/AminHonarmandiShandiz/cancerpredict

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Multimodal Deep Learning for Subtype Classification in Breast Cancer Using Histopathological Images and Gene Expression Data

https://github.com/BethanyL/damaged_cnns

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Modeling cognitive deficits following neurodegenerative diseases and traumatic brain injuries with deep convolutional neural networks

https://github.com/CUMC-Yuan-Lab/GCML/tree/main/SANet/BraTS

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Automatic Brain Tumor Segmentation with Scale Attention Network

https://github.com/Calvin-Pang/MAg

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MAg: a simple learning-based patient-level aggregation method for detecting microsatellite instability from whole-slide images

https://github.com/DarkoBomer/VCA-Net

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Stroke Lesion Segmentation with Visual Cortex Anatomy Alike Neural Nets

https://github.com/Eric-LRL/Brain-JEPA

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Brain-JEPA: Brain Dynamics Foundation Model with Gradient Positioning and Spatiotemporal Masking

https://github.com/Gollini/NSCLC_Radiogenomics

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A Radiogenomics Pipeline for Lung Nodules Segmentation and Prediction of EGFR Mutation Status from CT Scans

https://github.com/Guo-Xiaoqing/BraTS_OS

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Domain Knowledge Based Brain Tumor Segmentation and Overall Survival Prediction

https://github.com/JeroenGoedhart/EB_coBART_paper

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Co-data Learning for Bayesian Additive Regression Trees

https://github.com/LammertJ/RGT-Digital-Twin

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Large Language Models-Enabled Digital Twins for Precision Medicine in Rare Gynecological Tumors

https://github.com/MEDAL-IITB/MIDOG

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Improving Mitosis Detection Via UNet-based Adversarial Domain Homogenizer

https://github.com/PML-UCF/pinn

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Fleet Prognosis with Physics-informed Recurrent Neural Networks

https://github.com/Precision-Medical-Imaging-Group/BraTS2023-inferCode

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Model Ensemble for Brain Tumor Segmentation in Magnetic Resonance Imaging

https://github.com/Precision-Medical-Imaging-Group/BraTS2024-PEDS

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Magnetic Resonance Imaging Feature-Based Subtyping and Model Ensemble for Enhanced Brain Tumor Segmentation

https://github.com/RoonakR/Agitation_detection

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Semi-supervised Learning for Identifying the Likelihood of Agitation in People with Dementia

https://github.com/SZUHvern/D-UNet

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D-UNet: a dimension-fusion U shape network for chronic stroke lesion segmentation

https://github.com/Samiran-Dey/PathoGen

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Generating crossmodal gene expression from cancer histopathology improves multimodal AI predictions

https://github.com/ShawnBIT/Brain-Midline-Detection

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Context-Aware Refinement Network Incorporating Structural Connectivity Prior for Brain Midline Delineation

https://github.com/SiriusHou/DLRS_CVR_BAT-Deep-learning-enabled-brain-hemodynamic-mapping-using-resting-state-fMRI

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Deep-learning-enabled Brain Hemodynamic Mapping Using Resting-state fMRI

https://github.com/SiyuanYan1/PanDerm

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A Multimodal Vision Foundation Model for Clinical Dermatology

https://github.com/TPieciak/Stretched

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Q-space quantitative diffusion MRI measures using a stretched-exponential representation

https://github.com/Vadori/CytoArk

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HistoSmith: Single-Stage Histology Image-Label Generation via Conditional Latent Diffusion for Enhanced Cell Segmentation and Classification

https://github.com/Windbelll/Prognosis-analysis-of-cerebral-hemorrhage

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GCS-ICHNet: Assessment of Intracerebral Hemorrhage Prognosis using Self-Attention with Domain Knowledge Integration

https://github.com/Xiyue-Wang/RetCCL

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Analysis and Validation of Image Search Engines in Histopathology

https://github.com/YemanBrhane/AwareNet

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Cell abundance aware deep learning for cell detection on highly imbalanced pathological data

https://github.com/ZheLi2020/InfoDist

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Image Distillation for Safe Data Sharing in Histopathology

https://github.com/a-vzer/waveletflowpytorch

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Efficient Out-of-Distribution Detection of Melanoma with Wavelet-based Normalizing Flows

https://github.com/abner228/smilecode

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SimPLe: Similarity-Aware Propagation Learning for Weakly-Supervised Breast Cancer Segmentation in DCE-MRI

https://github.com/adaa-polsl/RuleKit

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Separate and conquer heuristic allows robust mining of contrast sets in classification, regression, and survival data

https://github.com/adamshephard/tiager

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TIAger: Tumor-Infiltrating Lymphocyte Scoring in Breast Cancer for the TiGER Challenge

https://github.com/ai4biomedicine/surgvae

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A Novel Generative Multi-Task Representation Learning Approach for Predicting Postoperative Complications in Cardiac Surgery Patients

https://github.com/ajv012/survpath

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Modeling Dense Multimodal Interactions Between Biological Pathways and Histology for Survival Prediction

https://github.com/akabircs/skin-lesions-classification

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An Attention-Guided Deep Learning Approach for Classifying 39 Skin Lesion Types

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.