Papers Specificity
“Specificity” 태그가 달린 논문 2,094편 · 필터 해제
RadiomicsRetrieval: A Customizable Framework for Medical Image Retrieval Using Radiomics Features
Medical image retrieval is a valuable field for supporting clinical decision-making, yet current methods primarily support 2D images and require fully annotated queries, limiting clinical flexibility. To address this, we…
Contrastive LearningImage RetrievalMedical Image RetrievalRetrieval+1PoseMaster: Generating 3D Characters in Arbitrary Poses from a Single Image
3D characters play a crucial role in our daily entertainment. To improve the efficiency of 3D character modeling, recent image-based methods use two separate models to achieve pose standardization and 3D reconstruction o…
3D ReconstructionSpecificityIMC-PINN-FE: A Physics-Informed Neural Network for Patient-Specific Left Ventricular Finite Element Modeling with Image Motion Consistency and Biomechanical Parameter Estimation
Elucidating the biomechanical behavior of the myocardium is crucial for understanding cardiac physiology, but cannot be directly inferred from clinical imaging and typically requires finite element (FE) simulations. Howe…
parameter estimationSpecificityPredicting Readiness to Engage in Psychotherapy of People with Chronic Pain Based on their Pain-Related Narratives Saar
Background. Chronic pain afflicts 20 % of the global population. A strictly biomedical mind-set leaves many sufferers chasing somatic cures and has fuelled the opioid crisis. The biopsychosocial model recognises pain sub…
Large Language ModelSensitivitySentenceSpecificityOn Context-Content Uncertainty Principle
The Context-Content Uncertainty Principle (CCUP) proposes that inference under uncertainty is governed by an entropy asymmetry between context and content: high-entropy contexts must be interpreted through alignment with…
SpecificityVisual-Semantic Knowledge Conflicts in Operating Rooms: Synthetic Data Curation for Surgical Risk Perception in Multimodal Large Language Models
Surgical risk identification is critical for patient safety and reducing preventable medical errors. While multimodal large language models (MLLMs) show promise for automated operating room (OR) risk detection, they ofte…
SpecificityWebGuard++:Interpretable Malicious URL Detection via Bidirectional Fusion of HTML Subgraphs and Multi-Scale Convolutional BERT
URL+HTML feature fusion shows promise for robust malicious URL detection, since attacker artifacts persist in DOM structures. However, prior work suffers from four critical shortcomings: (1) incomplete URL modeling, fail…
Contrastive LearningSpecificityModeling the influences of non-local connectomic projections on geometrically constrained cortical dynamics
The function and dynamics of the cortex are fundamentally shaped by the specific wiring configurations of its constituent axonal fibers, also known as the connectome. However, many dynamical properties of macroscale cort…
SpecificityA Modular Taxonomy for Hate Speech Definitions and Its Impact on Zero-Shot LLM Classification Performance
Detecting harmful content is a crucial task in the landscape of NLP applications for Social Good, with hate speech being one of its most dangerous forms. But what do we mean by hate speech, how can we define it, and how …
SpecificityA Deep Convolutional Neural Network-Based Novel Class Balancing for Imbalance Data Segmentation
Retinal fundus images provide valuable insights into the human eye's interior structure and crucial features, such as blood vessels, optic disk, macula, and fovea. However, accurate segmentation of retinal blood vessels …
SpecificityTransforming H&E images into IHC: A Variance-Penalized GAN for Precision Oncology
The overexpression of the human epidermal growth factor receptor 2 (HER2) in breast cells is a key driver of HER2-positive breast cancer, a highly aggressive subtype requiring precise diagnosis and targeted therapy. Immu…
Image-to-Image TranslationSpecificitySSIMCT Radiomics-Based Explainable Machine Learning Model for Accurate Differentiation of Malignant and Benign Endometrial Tumors: A Two-Center Study
Aimed to develop and validate a CT radiomics-based explainable machine learning model for diagnosing malignancy and benignity specifically in endometrial cancer (EC) patients. A total of 83 EC patients from two centers, …
DiagnosticSpecificityOmniESI: A unified framework for enzyme-substrate interaction prediction with progressive conditional deep learning
Understanding and modeling enzyme-substrate interactions is crucial for catalytic mechanism research, enzyme engineering, and metabolic engineering. Although a large number of predictive methods have emerged, they do not…
Parameter PredictionPredictionSpecificityA Prior-Guided Joint Diffusion Model in Projection Domain for PET Tracer Conversion
Positron emission tomography (PET) is widely used to assess metabolic activity, but its application is limited by the availability of radiotracers. 18F-labeled fluorodeoxyglucose (18F-FDG) is the most commonly used trace…
Image ReconstructionSpecificitySHREC and PHEONA: Using Large Language Models to Advance Next-Generation Computational Phenotyping
Objective: Computational phenotyping is a central informatics activity with resulting cohorts supporting a wide variety of applications. However, it is time-intensive because of manual data review, limited automation, an…
Computational PhenotypingPrompt EngineeringSpecificitytext-classification+1Detecting immune cells with label-free two-photon autofluorescence and deep learning
Label-free imaging has gained broad interest because of its potential to omit elaborate staining procedures which is especially relevant for in vivo use. Label-free multiphoton microscopy (MPM), for instance, exploits tw…
Binary ClassificationClassificationFADMulti-class Classification+1Uncertainty-Aware Deep Learning for Automated Skin Cancer Classification: A Comprehensive Evaluation
Accurate and reliable skin cancer diagnosis is critical for early treatment and improved patient outcomes. Deep learning (DL) models have shown promise in automating skin cancer classification, but their performance can …
Cancer ClassificationLesion ClassificationMedical DiagnosisSkin Cancer Classification+4ProtocolLLM: RTL Benchmark for SystemVerilog Generation of Communication Protocols
Recent advances in Large Language Models (LLMs) have shown promising capabilities in generating code for general-purpose programming languages. In contrast, their applicability for hardware description languages, particu…
Code GenerationSpecificitySingle-cell metabolic flux analysis reveals coexisting optimal sub-groups, cross-feeding, and mixotrophy in a cyanobacterial population
We derive a single-cell level understanding of metabolism in an isogenic cyanobacterial population by integrating secondary ion mass spectrometry (SIMS) derived multi-isotope uptake measurements of Synechocystis sp. PCC6…
SpecificityDIMCIM: A Quantitative Evaluation Framework for Default-mode Diversity and Generalization in Text-to-Image Generative Models
Recent advances in text-to-image (T2I) models have achieved impressive quality and consistency. However, this has come at the cost of representation diversity. While automatic evaluation methods exist for benchmarking mo…
BenchmarkingDiversityLarge Language ModelSpecificity