Phenotype classification
1개 벤치마크 · 논문 20편 · 이 태스크의 논문 보기 →
Benchmarks
MIMIC-CXR, MIMIC-IV
Most implemented
Multitask learning and benchmarking with clinical time series data
Merlin: A Vision Language Foundation Model for 3D Computed Tomography
TACCO: Task-guided Co-clustering of Clinical Concepts and Patient Visits for Disease Subtyping based on EHR Data
MedFuse: Multi-modal fusion with clinical time-series data and chest X-ray images
Enriching Unsupervised User Embedding via Medical Concepts
Papers
Hierarchical Specialised Ensembles for Classification of Zebrafish Phenotypes Using the Selected Image Recognition Methods
We propose and evaluate three hierarchical ensemble setups for zebrafish phenotype classification from embryo images. In all setups, stage 1 uses a single four-class classifier to assign images to one of the exclusive ph…
Phenotype classificationHierarchical Classification via Cascading Feature Elimination: Application to Human Phenotype Ontology-Aligned Facial Phenotyping (FaceMesh2HPO)
FaceMesh2HPO is a framework for classifying facial phenotypic descriptors aligned with the Human Phenotype Ontology (HPO) to support clinical diagnosis. Using annotations from 124 clinicians across 10 disorders (107 HPO …
Phenotype classificationLatent World Recovery for Multimodal Learning with Missing Modalities
We study multimodal learning under missing modalities, with particular motivation from bioscience applications in which heterogeneous modalities are often only partially available when decisions need to be made. We propo…
Phenotype classificationRepresentation LearningResGene-T: A Tensor-Based Residual Network Approach for Genomic Prediction
In this work, we propose a new deep learning model for Genomic Prediction (GP), which involves correlating genotypic data with phenotypic. The genotypes are typically fed as a sequence of characters to the 1D-Convolution…
Phenotype classificationPhenoLIP: Integrating Phenotype Ontology Knowledge into Medical Vision-Language Pretraining
Recent progress in large-scale CLIP-like vision-language models(VLMs) has greatly advanced medical image analysis. However, most existing medical VLMs still rely on coarse image-text contrastive objectives and fail to ca…
Phenotype classificationKnowledge DistillationCross-Modal RetrievalGenerative diffusion models for agricultural AI: plant image generation, indoor-to-outdoor translation, and expert preference alignment
The success of agricultural artificial intelligence depends heavily on large, diverse, and high-quality plant image datasets, yet collecting such data in real field conditions is costly, labor intensive, and seasonally c…
Phenotype classificationImage Generation