Papers with Code 아카이브

Predictive Process Monitoring

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A branch of predictive analysis that attempts to predict some future state of a business process.

코드

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

https://github.com/jiazhang93/segmentation

공식 코드

Whole-Body Lesion Segmentation in 18F-FDG PET/CT

https://github.com/jieWeiLu/Strabismus-Detection-for-Telemedicine-Application

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Automated Strabismus Detection for Telemedicine Applications

https://github.com/jmnolte/hccnet

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A CNN-Transformer for Classification of Longitudinal 3D MRI Images -- A Case Study on Hepatocellular Carcinoma Prediction

https://github.com/jonghyeonk/kb-modulation

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Knowledge-Driven Modulation of Neural Networks with Attention Mechanism for Next Activity Prediction

https://github.com/jsb-ucla/itca

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Information-theoretic Classification Accuracy: A Criterion that Guides Data-driven Combination of Ambiguous Outcome Labels in Multi-class Classification

https://github.com/jsh0792/mcti

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Multimodal Cross-Task Interaction for Survival Analysis in Whole Slide Pathological Images

https://github.com/jsliam94/cmswinkan

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Towards Accurate and Interpretable Neuroblastoma Diagnosis via Contrastive Multi-scale Pathological Image Analysis

https://github.com/junfish/Awesome-Multitask-Learning

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Unleashing the Power of Multi-Task Learning: A Comprehensive Survey Spanning Traditional, Deep, and Pretrained Foundation Model Eras

https://github.com/junjianli106/mico

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MiCo: Multiple Instance Learning with Context-Aware Clustering for Whole Slide Image Analysis

https://github.com/knowlab/daindex-framework

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Quantifying Health Inequalities Induced by Data and AI Models

https://github.com/lbasyal/Histopathologic-Cancer-Detection-

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Histopathologic Cancer Detection

https://github.com/learner-codec/autoprom_sam

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Pathological Primitive Segmentation Based on Visual Foundation Model with Zero-Shot Mask Generation

https://github.com/leomlck/medimp

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MEDIMP: 3D Medical Images with clinical Prompts from limited tabular data for renal transplantation

https://github.com/leooo-shen/tvrl

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Spatiotemporal Representation Learning for Short and Long Medical Image Time Series

https://github.com/lhy1007/m3c2

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Joint Modelling Histology and Molecular Markers for Cancer Classification

https://github.com/liupei101/DSCA

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DSCA: A Dual-Stream Network with Cross-Attention on Whole-Slide Image Pyramids for Cancer Prognosis

https://github.com/liupei101/advmil

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AdvMIL: Adversarial Multiple Instance Learning for the Survival Analysis on Whole-Slide Images

https://github.com/liupei101/vlsa

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Interpretable Vision-Language Survival Analysis with Ordinal Inductive Bias for Computational Pathology

https://github.com/lkpengcs/syntumoranalyzer

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Optimizing Synthetic Data for Enhanced Pancreatic Tumor Segmentation

https://github.com/lmxmercy/mgct

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MGCT: Mutual-Guided Cross-Modality Transformer for Survival Outcome Prediction using Integrative Histopathology-Genomic Features

https://github.com/lucas-rbnt/drim

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DRIM: Learning Disentangled Representations from Incomplete Multimodal Healthcare Data

https://github.com/luchang-cs/chet

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Context-aware Health Event Prediction via Transition Functions on Dynamic Disease Graphs

https://github.com/ma3oun/gbheterogeneity

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Uncovering the Genetic Basis of Glioblastoma Heterogeneity through Multimodal Analysis of Whole Slide Images and RNA Sequencing Data

https://github.com/mahmoodlab/FISH

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Fast and Scalable Image Search For Histology

https://github.com/mahmoodlab/PORPOISE

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Pan-Cancer Integrative Histology-Genomic Analysis via Interpretable Multimodal Deep Learning

https://github.com/mahmoodlab/PathomicFusion

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Pathomic Fusion: An Integrated Framework for Fusing Histopathology and Genomic Features for Cancer Diagnosis and Prognosis

https://github.com/mahmoodlab/mamba

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Weakly Supervised AI for Efficient Analysis of 3D Pathology Samples

https://github.com/mahmoodlab/survpath

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

https://github.com/mahmoodlab/titan

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Multimodal Whole Slide Foundation Model for Pathology

https://github.com/marrlab/ae-cfe

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Unsupervised Cross-Domain Feature Extraction for Single Blood Cell Image Classification

https://github.com/mateoespinosa/remix

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Efficient Decompositional Rule Extraction for Deep Neural Networks

https://github.com/matteochieregato/GradientboostingCovid19

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A hybrid machine learning/deep learning COVID-19 severity predictive model from CT images and clinical data

https://github.com/maxhallemeesch/praline

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Prior Knowledge Injection into Deep Learning Models Predicting Gene Expression from Whole Slide Images

https://github.com/mdciri/Vox2Vox

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Vox2Vox: 3D-GAN for Brain Tumour Segmentation

https://github.com/mdsatria/multiattentionmil

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Multi-Scale Attention-based Multiple Instance Learning for Classification of Multi-Gigapixel Histology Images

https://github.com/menggersherry/gene-moe

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Gene-MOE: A sparsely gated prognosis and classification framework exploiting pan-cancer genomic information

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