Papers Prognosis
“Prognosis” 태그가 달린 논문 900편 · 필터 해제
Site-Level Fine-Tuning with Progressive Layer Freezing: Towards Robust Prediction of Bronchopulmonary Dysplasia from Day-1 Chest Radiographs in Extremely Preterm Infants
Bronchopulmonary dysplasia (BPD) is a chronic lung disease affecting 35% of extremely low birth weight infants. Defined by oxygen dependence at 36 weeks postmenstrual age, it causes lifelong respiratory complications. Ho…
Federated LearningPrognosisLearning Disentangled Stain and Structural Representations for Semi-Supervised Histopathology Segmentation
Accurate gland segmentation in histopathology images is essential for cancer diagnosis and prognosis. However, significant variability in Hematoxylin and Eosin (H&E) staining and tissue morphology, combined with limited …
PrognosisSegmentationSegment Anything in Pathology Images with Natural Language
Pathology image segmentation is crucial in computational pathology for analyzing histological features relevant to cancer diagnosis and prognosis. However, current methods face major challenges in clinical applications d…
DiagnosticFeature ImportanceImage SegmentationPrognosis+2[Beat-to-beat AV nodal assessment] ECG-based beat-to-beat assessment of AV node conduction properties during AF
The refractory period and conduction delay of the atrioventricular (AV) node play a crucial role in regulating the heart rate during atrial fibrillation (AF). Beat-to-beat variations in these properties are known to be i…
PrognosisMiCo: Multiple Instance Learning with Context-Aware Clustering for Whole Slide Image Analysis
Multiple instance learning (MIL) has shown significant promise in histopathology whole slide image (WSI) analysis for cancer diagnosis and prognosis. However, the inherent spatial heterogeneity of WSIs presents critical …
ClusteringMultiple Instance LearningPrognosisUniversal Laboratory Model: prognosis of abnormal clinical outcomes based on routine tests
Clinical laboratory results are ubiquitous in any diagnosis making. Predicting abnormal values of not prescribed tests based on the results of performed tests looks intriguing, as it would be possible to make early diagn…
CBC TESTMissing ValuesPrognosisOptimized Spectral Fault Receptive Fields for Diagnosis-Informed Prognosis
This paper introduces Spectral Fault Receptive Fields (SFRFs), a biologically inspired technique for degradation state assessment in bearing fault diagnosis and remaining useful life (RUL) estimation. Drawing on the cent…
Fault DiagnosisPrognosisImproving Oral Cancer Outcomes Through Machine Learning and Dimensionality Reduction
Oral cancer presents a formidable challenge in oncology, necessitating early diagnosis and accurate prognosis to enhance patient survival rates. Recent advancements in machine learning and data mining have revolutionized…
DiagnosticDimensionality ReductionEnsemble Learningfeature selection+1ADAgent: LLM Agent for Alzheimer's Disease Analysis with Collaborative Coordinator
Alzheimer's disease (AD) is a progressive and irreversible neurodegenerative disease. Early and precise diagnosis of AD is crucial for timely intervention and treatment planning to alleviate the progressive neurodegenera…
AI AgentLarge Language ModelPrognosisA Narrative Review on Large AI Models in Lung Cancer Screening, Diagnosis, and Treatment Planning
Lung cancer remains one of the most prevalent and fatal diseases worldwide, demanding accurate and timely diagnosis and treatment. Recent advancements in large AI models have significantly enhanced medical image understa…
Decision MakingDecoderPrognosisNSUN2 as a potential prognostic as well as therapeutic target in cancer by regulating m5C modification
m5C modification is a type of RNA methylation modification, and its major methyltransferase, NSUN2, catalyzes m5C modification. NSUN2 is overexpressed in a variety of cancers, and it affects the metabolism of RNA from ta…
PrognosisCausal Explainability of Machine Learning in Heart Failure Prediction from Electronic Health Records
The importance of clinical variables in the prognosis of the disease is explained using statistical correlation or machine learning (ML). However, the predictive importance of these variables may not represent their caus…
Causal DiscoveryFeature ImportancePrognosisRevisiting End-to-End Learning with Slide-level Supervision in Computational Pathology
Pre-trained encoders for offline feature extraction followed by multiple instance learning (MIL) aggregators have become the dominant paradigm in computational pathology (CPath), benefiting cancer diagnosis and prognosis…
Multiple Instance LearningPrognosispetBrain: A New Pipeline for Amyloid, Tau Tangles and Neurodegeneration Quantification Using PET and MRI
INTRODUCTION: Quantification of amyloid plaques (A), neurofibrillary tangles (T2), and neurodegeneration (N) using PET and MRI is critical for Alzheimer's disease (AD) diagnosis and prognosis. Existing pipelines face lim…
PrognosisInterpretable phenotyping of Heart Failure patients with Dutch discharge letters
Objective: Heart failure (HF) patients present with diverse phenotypes affecting treatment and prognosis. This study evaluates models for phenotyping HF patients based on left ventricular ejection fraction (LVEF) classes…
PrognosisConfLUNet: Multiple sclerosis lesion instance segmentation in presence of confluent lesions
Accurate lesion-level segmentation on MRI is critical for multiple sclerosis (MS) diagnosis, prognosis, and disease monitoring. However, current evaluation practices largely rely on semantic segmentation post-processed w…
Instance SegmentationLesion DetectionPrognosisSegmentation+1Subspecialty-Specific Foundation Model for Intelligent Gastrointestinal Pathology
Gastrointestinal (GI) diseases represent a clinically significant burden, necessitating precise diagnostic approaches to optimize patient outcomes. Conventional histopathological diagnosis suffers from limited reproducib…
DiagnosticPrognosiswhole slide imagesCardiac Digital Twins at Scale from MRI: Open Tools and Representative Models from ~55000 UK Biobank Participants
A cardiac digital twin is a virtual replica of a patient's heart for screening, diagnosis, prognosis, risk assessment, and treatment planning of cardiovascular diseases. This requires an anatomically accurate patient-spe…
PrognosisBeyond Segmentation: Confidence-Aware and Debiased Estimation of Ratio-based Biomarkers
Ratio-based biomarkers -- such as the proportion of necrotic tissue within a tumor -- are widely used in clinical practice to support diagnosis, prognosis and treatment planning. These biomarkers are typically estimated …
Decision MakingPrognosisPathBench: A comprehensive comparison benchmark for pathology foundation models towards precision oncology
The emergence of pathology foundation models has revolutionized computational histopathology, enabling highly accurate, generalized whole-slide image analysis for improved cancer diagnosis, and prognosis assessment. Whil…
BenchmarkingPrognosis