Papers with Code 아카이브

Predictive Process Monitoring

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

전체 기법 전체 데이터셋

하위 태스크: 1
평가표: 0
보존된 평가 기록: 0

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/adamshephard/tiager

공식 코드

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

https://github.com/ai4biomedicine/surgvae

공식 코드

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

https://github.com/ajv012/survpath

공식 코드

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

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

공식 코드

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

https://github.com/amarquand/nispat

공식 코드

Hierarchical Bayesian Regression for Multi-Site Normative Modeling of Neuroimaging Data

https://github.com/aniketmaurya/covid-research

공식 코드

Predicting intubation support requirement of patients using Chest X-ray with Deep Representation Learning

https://github.com/auranic/ClinTrajan

공식 코드

Trajectories, bifurcations and pseudotime in large clinical datasets: applications to myocardial infarction and diabetes data

https://github.com/awaisali37405/lstm---daemon-action

공식 코드

Enhancing the Accuracy of Predictors of Activity Sequences of Business Processes

https://github.com/ayanglab/dmib

공식 코드

Dynamic Multimodal Information Bottleneck for Multimodality Classification

https://github.com/basiralab/RG-Select

공식 코드

Quantifying the Reproducibility of Graph Neural Networks using Multigraph Brain Data

https://github.com/bigchem/transformer-cnn

공식 코드

Transformer-CNN: Fast and Reliable tool for QSAR

https://github.com/binging512/umpsnet

공식 코드

A Multi-Modal Deep Learning Framework for Pan-Cancer Prognosis

https://github.com/biomedia-mbzuai/hulp

공식 코드

HuLP: Human-in-the-Loop for Prognosis

https://github.com/bionlplab/longitudinal_transformer_for_survival_analysis

공식 코드

Harnessing the power of longitudinal medical imaging for eye disease prognosis using Transformer-based sequence modeling

https://github.com/bmirds/wsi-plp

공식 코드

Masked Pre-Training of Transformers for Histology Image Analysis

https://github.com/caiguohui123/awesome-lung-cancer-detection

공식 코드

Medical Artificial Intelligence for Early Detection of Lung Cancer: A Survey

https://github.com/caixdlab/cl4capro

공식 코드

Contrastive Learning for Predicting Cancer Prognosis Using Gene Expression Values

https://github.com/caodoanh2001/FALFormer

공식 코드

FALFormer: Feature-aware Landmarks self-attention for Whole-slide Image Classification

https://github.com/cdttk/biv-volumetric-meshing

공식 코드

Cardiac Digital Twins at Scale from MRI: Open Tools and Representative Models from ~55000 UK Biobank Participants

https://github.com/chimeraki/Multilayer-Trajectory-Clustering

공식 코드

Multi-layer Trajectory Clustering: A Network Algorithm for Disease Subtyping

https://github.com/christopher-irw/proformer_ce

공식 코드

Structural Positional Encoding for knowledge integration in transformer-based medical process monitoring

https://github.com/chulmoon/TopologicalTumorShape

공식 코드

Using Persistent Homology Topological Features to Characterize Medical Images: Case Studies on Lung and Brain Cancers

https://github.com/cmhimself/quest

공식 코드

Querying functional and structural niches on spatial transcriptomics data

https://github.com/cohenyo/xai-clustering-phm

공식 코드

Shapley-based Explainable AI for Clustering Applications in Fault Diagnosis and Prognosis

https://github.com/cpystan/wsi-vqa

공식 코드

WSI-VQA: Interpreting Whole Slide Images by Generative Visual Question Answering

https://github.com/cvblab/self_learning_wsi_prostate

공식 코드

Self-learning for weakly supervised Gleason grading of local patterns

https://github.com/dbouget/Raidionics

공식 코드

Preoperative brain tumor imaging: models and software for segmentation and standardized reporting

https://github.com/dbouget/Raidionics-Slicer

공식 코드

Preoperative brain tumor imaging: models and software for segmentation and standardized reporting

https://github.com/dbouget/validation_metrics_computation

공식 코드

Preoperative brain tumor imaging: models and software for segmentation and standardized reporting

https://github.com/dearcaat/e2e-wsi-abmilx

공식 코드

Revisiting End-to-End Learning with Slide-level Supervision in Computational Pathology

https://github.com/dearcaat/rrt-mil

공식 코드

Feature Re-Embedding: Towards Foundation Model-Level Performance in Computational Pathology

https://github.com/dl4mhealth/ts-contrastive-augmentation-recommendation

공식 코드

Guidelines for Augmentation Selection in Contrastive Learning for Time Series Classification

https://github.com/dorothy-yao/drfuse

공식 코드

DrFuse: Learning Disentangled Representation for Clinical Multi-Modal Fusion with Missing Modality and Modal Inconsistency

https://github.com/dougpsg/covid_mavidh_icufeatures_scoring

공식 코드

MAVIDH Score: A COVID-19 Severity Scoring using Chest X-Ray Pathology Features

https://github.com/embedded-robotics/path-rag

공식 코드

Path-RAG: Knowledge-Guided Key Region Retrieval for Open-ended Pathology Visual Question Answering

https://github.com/erellgachon/cytolot

공식 코드

Low dimensional representation of multi-patient flow cytometry datasets using optimal transport for minimal residual disease detection in leukemia

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