{"about":{"non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","site":"https://codewithpapers.app","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page","syntology":{"site":"https://syntology.ai","developers":"https://syntology.ai/developers","mcp":{"server":"https://syntology.ai/mcp","transport":"streamable-http","server_card":"https://syntology.ai/.well-known/mcp/server-card.json","auth":{"type":"trial token, no account","trial_token":"https://syntology.ai/api/oauth/trial/token","method":"POST","docs":"https://syntology.ai/developers"}},"have":"https://syntology.ai/api/graph/have?x=<method, arXiv id or title> (free, answers coverage only)","paper_base":"https://syntology.ai/paper/","atlas_base":"https://app.syntology.ai/?focus="},"machine_readable":[{"url":"https://codewithpapers.app/llms.txt","what":"the machine catalog: every machine-readable file, counted"},{"url":"https://codewithpapers.app/index/manifest.json","what":"paper-to-code index by arXiv id, with Syntology's counts"},{"url":"https://codewithpapers.app/search/manifest.json","what":"site search index (titles, authors) and its files"},{"url":"https://codewithpapers.app/download","what":"bulk files: Syntology's layer, described there"},{"url":"https://codewithpapers.app/build_manifest.json","what":"the build record: inputs, counts, exclusions, probes"}]},"url":"/task/diagnostic/papers/18","list_of":"/task/diagnostic","task":"Diagnostic","archive":{"snapshot":"2025-07-28"},"key_notes":{"n_ran_checked":"legacy name, kept unchanged so existing readers do not break: it counts the samples that ran with no instrument failure (honoured, violated, and ran with no contract checked); it does not mean a contract was checked, and the pages print it as 'K with no instrument failure', not 'K checked'","n_constructed":"a sub-count of the samples that ran, never subtracted from them and never a failure: an executed sample whose run returned an instance of its own class (fixture_out_type equals the entry name): the run built an object and did not compute a result (Syntology's RAN record, counts.constructed)"},"syntology_read_at":"2026-09-28T10:30:06+00:00","order":"archive","order_definition":"repositories listed in the archive (most first), then date (newest first), then slug","page":18,"pages_in_order":46,"rows_per_page":100,"rows":[1701,1800],"of":4513,"counts":{"archive_papers_tagged":4513,"with_a_code_link":1213,"where_syntology_ran_a_sample":157,"not_listed_spam_title":0,"listed":4513,"listed_where_code_ran":157,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":132,"every_run_a_failure_of_syntologys_instrument":25,"listed_with_a_run_with_no_instrument_failure":132,"listed_every_run_a_failure_of_syntologys_instrument":25,"filter":{"states":["a run with no instrument failure","any run, instrument failures included"],"default":"a run with no instrument failure","note":"on the 'only where code ran' pages the default hides, in the browser, the rows where every run was a failure of Syntology's instrument; the second state shows them again. Rows are hidden, never re-ordered; these twins list every row"}},"definition":"distinct papers the archive tags; 'where Syntology ran a sample' counts papers with at least one harvested sample that ran, which is not a correctness claim"},"first_page":"/task/diagnostic","prev":"/task/diagnostic/papers/17","next":"/task/diagnostic/papers/19","papers":[{"url":null,"slug":"glioma-multimodal-mri-analysis-system-for","title":"Glioma Multimodal MRI Analysis System for Tumor Layered Diagnosis via Multi-task Semi-supervised Learning","date":"2025-01-29","arxiv_id":"2501.17758","repositories_listed":0,"syntology":null},{"url":null,"slug":"llm-assistance-for-pediatric-depression","title":"LLM Assistance for Pediatric Depression","date":"2025-01-29","arxiv_id":"2501.17510","repositories_listed":0,"syntology":null},{"url":null,"slug":"trustworthy-image-to-image-translation","title":"Trustworthy image-to-image translation: evaluating uncertainty calibration in unpaired training scenarios","date":"2025-01-29","arxiv_id":"2501.17570","repositories_listed":0,"syntology":null},{"url":null,"slug":"fine-tuning-open-source-large-language-models","title":"Fine-Tuning Open-Source Large Language Models to Improve Their Performance on Radiation Oncology Tasks: A Feasibility Study to Investigate Their Potential Clinical Applications in Radiation Oncology","date":"2025-01-28","arxiv_id":"2501.17286","repositories_listed":0,"syntology":null},{"url":null,"slug":"automatic-feedback-generation-for-short","title":"Automatic Feedback Generation for Short Answer Questions using Answer Diagnostic Graphs","date":"2025-01-27","arxiv_id":"2501.15777","repositories_listed":0,"syntology":null},{"url":null,"slug":"brain-adapter-enhancing-neurological-disorder","title":"Brain-Adapter: Enhancing Neurological Disorder Analysis with Adapter-Tuning Multimodal Large Language Models","date":"2025-01-27","arxiv_id":"2501.16282","repositories_listed":0,"syntology":null},{"url":null,"slug":"ai-in-oncology-transforming-cancer-detection","title":"AI in Oncology: Transforming Cancer Detection through Machine Learning and Deep Learning Applications","date":"2025-01-26","arxiv_id":"2501.15489","repositories_listed":0,"syntology":null},{"url":null,"slug":"breaking-the-stigma-unobtrusively-probe","title":"Breaking the Stigma! Unobtrusively Probe Symptoms in Depression Disorder Diagnosis Dialogue","date":"2025-01-25","arxiv_id":"2501.15260","repositories_listed":0,"syntology":null},{"url":null,"slug":"fusion-of-millimeter-wave-radar-and-pulse","title":"Fusion of Millimeter-wave Radar and Pulse Oximeter Data for Low-burden Diagnosis of Obstructive Sleep Apnea-Hypopnea Syndrome","date":"2025-01-25","arxiv_id":"2501.15264","repositories_listed":0,"syntology":null},{"url":null,"slug":"approach-to-designing-cv-systems-for-medical","title":"Approach to Designing CV Systems for Medical Applications: Data, Architecture and AI","date":"2025-01-24","arxiv_id":"2501.14689","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-learning-powered-classification-of","title":"Deep Learning-Powered Classification of Thoracic Diseases in Chest X-Rays","date":"2025-01-24","arxiv_id":"2501.14279","repositories_listed":0,"syntology":null},{"url":null,"slug":"distinguishing-parkinson-s-patients-using","title":"Distinguishing Parkinson's Patients Using Voice-Based Feature Extraction and Classification","date":"2025-01-24","arxiv_id":"2501.14390","repositories_listed":0,"syntology":null},{"url":null,"slug":"hybrid-interpretable-deep-learning-framework","title":"Hybrid Interpretable Deep Learning Framework for Skin Cancer Diagnosis: Integrating Radial Basis Function Networks with Explainable AI","date":"2025-01-24","arxiv_id":"2501.14885","repositories_listed":0,"syntology":null},{"url":null,"slug":"prompt-based-cost-effective-evaluation-and","title":"Prompt-Based Cost-Effective Evaluation and Operation of ChatGPT as a Computer Programming Teaching Assistant","date":"2025-01-24","arxiv_id":"2501.17176","repositories_listed":0,"syntology":null},{"url":null,"slug":"review-and-recommendations-for-using","title":"Review and Recommendations for using Artificial Intelligence in Intracoronary Optical Coherence Tomography Analysis","date":"2025-01-24","arxiv_id":"2501.18614","repositories_listed":0,"syntology":null},{"url":null,"slug":"sparse-mixture-of-experts-for-non-uniform","title":"Sparse Mixture-of-Experts for Non-Uniform Noise Reduction in MRI Images","date":"2025-01-24","arxiv_id":"2501.14198","repositories_listed":0,"syntology":null},{"url":"/paper/cognitive-paradigms-for-evaluating-vlms-on","slug":"cognitive-paradigms-for-evaluating-vlms-on","title":"A Cognitive Paradigm Approach to Probe the Perception-Reasoning Interface in VLMs","date":"2025-01-23","arxiv_id":"2501.13620","repositories_listed":0,"syntology":null},{"url":null,"slug":"comprehensive-modeling-and-question-answering","title":"Comprehensive Modeling and Question Answering of Cancer Clinical Practice Guidelines using LLMs","date":"2025-01-23","arxiv_id":"2501.13984","repositories_listed":0,"syntology":null},{"url":null,"slug":"skin-disease-detection-and-classification-of","title":"Skin Disease Detection and Classification of Actinic Keratosis and Psoriasis Utilizing Deep Transfer Learning","date":"2025-01-23","arxiv_id":"2501.13713","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-novel-tracking-framework-for-devices-in-x","title":"A Novel Tracking Framework for Devices in X-ray Leveraging Supplementary Cue-Driven Self-Supervised Features","date":"2025-01-22","arxiv_id":"2501.12958","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-selective-homomorphic-encryption-approach","title":"A Selective Homomorphic Encryption Approach for Faster Privacy-Preserving Federated Learning","date":"2025-01-22","arxiv_id":"2501.12911","repositories_listed":0,"syntology":null},{"url":null,"slug":"computational-modelling-of-biological-systems","title":"Computational modelling of biological systems now and then: revisiting tools and visions from the beginning of the century","date":"2025-01-22","arxiv_id":"2501.13142","repositories_listed":0,"syntology":null},{"url":null,"slug":"multi-stage-intermediate-fusion-for","title":"Multi-stage intermediate fusion for multimodal learning to classify non-small cell lung cancer subtypes from CT and PET","date":"2025-01-21","arxiv_id":"2501.12425","repositories_listed":0,"syntology":null},{"url":null,"slug":"scalable-whole-slide-image-representation","title":"Scalable Whole Slide Image Representation Using K-Mean Clustering and Fisher Vector Aggregation","date":"2025-01-21","arxiv_id":"2501.12085","repositories_listed":0,"syntology":null},{"url":null,"slug":"vision-language-models-for-automated-chest-x","title":"Vision-Language Models for Automated Chest X-ray Interpretation: Leveraging ViT and GPT-2","date":"2025-01-21","arxiv_id":"2501.12356","repositories_listed":0,"syntology":null},{"url":null,"slug":"evolutionary-independent-deterministic","title":"EVolutionary Independent DEtermiNistiC Explanation","date":"2025-01-20","arxiv_id":"2501.16357","repositories_listed":0,"syntology":null},{"url":null,"slug":"an-analysis-of-the-combination-of-feature","title":"An analysis of the combination of feature selection and machine learning methods for an accurate and timely detection of lung cancer","date":"2025-01-19","arxiv_id":"2501.10980","repositories_listed":0,"syntology":null},{"url":null,"slug":"transfer-learning-strategies-for-pathological","title":"Transfer Learning Strategies for Pathological Foundation Models: A Systematic Evaluation in Brain Tumor Classification","date":"2025-01-19","arxiv_id":"2501.11014","repositories_listed":0,"syntology":null},{"url":null,"slug":"enhancing-diagnostic-in-3d-covid-19-pneumonia","title":"Enhancing Diagnostic in 3D COVID-19 Pneumonia CT-scans through Explainable Uncertainty Bayesian Quantification","date":"2025-01-18","arxiv_id":"2501.10770","repositories_listed":0,"syntology":null},{"url":null,"slug":"accept-diagnostic-forecasting-of-battery","title":"ACCEPT: Diagnostic Forecasting of Battery Degradation Through Contrastive Learning","date":"2025-01-17","arxiv_id":"2501.10492","repositories_listed":0,"syntology":null},{"url":null,"slug":"fect-classification-of-breast-cancer","title":"FECT: Classification of Breast Cancer Pathological Images Based on Fusion Features","date":"2025-01-17","arxiv_id":"2501.10128","repositories_listed":0,"syntology":null},{"url":null,"slug":"detection-of-vascular-leukoencephalopathy-in","title":"Detection of Vascular Leukoencephalopathy in CT Images","date":"2025-01-16","arxiv_id":"2501.09863","repositories_listed":0,"syntology":null},{"url":null,"slug":"estimating-task-based-performance-bounds-for","title":"Estimating Task-based Performance Bounds for Accelerated MRI Image Reconstruction Methods by Use of Learned-Ideal Observers","date":"2025-01-16","arxiv_id":"2501.09224","repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-hemodynamic-scalar-fields-on","title":"Learning Hemodynamic Scalar Fields on Coronary Artery Meshes: A Benchmark of Geometric Deep Learning Models","date":"2025-01-15","arxiv_id":"2501.09046","repositories_listed":0,"syntology":null},{"url":null,"slug":"exploring-visual-language-models-as-a","title":"Exploring visual language models as a powerful tool in the diagnosis of Ewing Sarcoma","date":"2025-01-14","arxiv_id":"2501.08042","repositories_listed":0,"syntology":null},{"url":null,"slug":"head-motion-degrades-machine-learning","title":"Head Motion Degrades Machine Learning Classification of Alzheimer's Disease from Positron Emission Tomography","date":"2025-01-14","arxiv_id":"2501.08459","repositories_listed":0,"syntology":null},{"url":null,"slug":"boosting-sclera-segmentation-through-semi","title":"Boosting Sclera Segmentation through Semi-supervised Learning with Fewer Labels","date":"2025-01-13","arxiv_id":"2501.07750","repositories_listed":0,"syntology":null},{"url":null,"slug":"cds-data-synthesis-method-guided-by-cognitive","title":"CDS: Data Synthesis Method Guided by Cognitive Diagnosis Theory","date":"2025-01-13","arxiv_id":"2501.07674","repositories_listed":0,"syntology":null},{"url":null,"slug":"knowledge-distillation-and-enhanced-subdomain","title":"Knowledge Distillation and Enhanced Subdomain Adaptation Using Graph Convolutional Network for Resource-Constrained Bearing Fault Diagnosis","date":"2025-01-13","arxiv_id":"2501.07173","repositories_listed":0,"syntology":null},{"url":null,"slug":"large-language-models-for-interpretable","title":"Large Language Models for Interpretable Mental Health Diagnosis","date":"2025-01-13","arxiv_id":"2501.07653","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-comprehensive-evaluation-of-large-language-5","title":"A Comprehensive Evaluation of Large Language Models on Mental Illnesses in Arabic Context","date":"2025-01-12","arxiv_id":"2501.06859","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-foundational-generative-model-for-breast","title":"A Foundational Generative Model for Breast Ultrasound Image Analysis","date":"2025-01-12","arxiv_id":"2501.06869","repositories_listed":0,"syntology":null},{"url":null,"slug":"medgrad-e-clip-enhancing-trust-and","title":"MedGrad E-CLIP: Enhancing Trust and Transparency in AI-Driven Skin Lesion Diagnosis","date":"2025-01-12","arxiv_id":"2501.06887","repositories_listed":0,"syntology":null},{"url":null,"slug":"medct-a-clinical-terminology-graph-for","title":"MedCT: A Clinical Terminology Graph for Generative AI Applications in Healthcare","date":"2025-01-11","arxiv_id":"2501.06465","repositories_listed":0,"syntology":null},{"url":null,"slug":"ai-driven-diabetic-retinopathy-screening","title":"AI-Driven Diabetic Retinopathy Screening: Multicentric Validation of AIDRSS in India","date":"2025-01-10","arxiv_id":"2501.05826","repositories_listed":0,"syntology":null},{"url":null,"slug":"swin-x2s-reconstructing-3d-shape-from-2d","title":"Swin-X2S: Reconstructing 3D Shape from 2D Biplanar X-ray with Swin Transformers","date":"2025-01-10","arxiv_id":"2501.05961","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-ct-image-classification-network-framework","title":"A CT Image Classification Network Framework for Lung Tumors Based on Pre-trained MobileNetV2 Model and Transfer learning, And Its Application and Market Analysis in the Medical field","date":"2025-01-09","arxiv_id":"2501.04996","repositories_listed":0,"syntology":null},{"url":null,"slug":"from-images-to-insights-transforming-brain","title":"From Images to Insights: Transforming Brain Cancer Diagnosis with Explainable AI","date":"2025-01-09","arxiv_id":"2501.05426","repositories_listed":0,"syntology":null},{"url":null,"slug":"world-of-scorecraft-novel-multi-scorer","title":"World of ScoreCraft: Novel Multi Scorer Experiment on the Impact of a Decision Support System in Sleep Staging","date":"2025-01-09","arxiv_id":"2503.15492","repositories_listed":0,"syntology":null},{"url":null,"slug":"machine-learning-and-statistical","title":"Machine Learning and statistical classification of CRISPR-Cas12a diagnostic assays","date":"2025-01-08","arxiv_id":"2501.04413","repositories_listed":0,"syntology":null},{"url":null,"slug":"medcodi-m-a-multi-prompt-foundation-model-for","title":"MedCoDi-M: A Multi-Prompt Foundation Model for Multimodal Medical Data Generation","date":"2025-01-08","arxiv_id":"2501.04614","repositories_listed":0,"syntology":null},{"url":null,"slug":"quantum-hybrid-support-vector-machines-for","title":"Quantum Hybrid Support Vector Machines for Stress Detection in Older Adults","date":"2025-01-08","arxiv_id":"2501.04831","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-multimodal-lightweight-approach-to-fault","title":"A Multimodal Lightweight Approach to Fault Diagnosis of Induction Motors in High-Dimensional Dataset","date":"2025-01-07","arxiv_id":"2501.03746","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-learning-for-ophthalmology-the-state-of","title":"Deep Learning for Ophthalmology: The State-of-the-Art and Future Trends","date":"2025-01-07","arxiv_id":"2501.04073","repositories_listed":0,"syntology":null},{"url":null,"slug":"towards-a-generalizable-speech-marker-for","title":"Towards a Generalizable Speech Marker for Parkinson's Disease Diagnosis","date":"2025-01-07","arxiv_id":"2501.03581","repositories_listed":0,"syntology":null},{"url":"/paper/coph100-a-comprehensive-fundus-image","slug":"coph100-a-comprehensive-fundus-image","title":"COph100: A comprehensive fundus image registration dataset from infants constituting the \"RIDIRP\" database","date":"2025-01-06","arxiv_id":"2501.02800","repositories_listed":0,"syntology":null},{"url":null,"slug":"hybrid-deep-convolution-model-for-lung-cancer","title":"Hybrid deep convolution model for lung cancer detection with transfer learning","date":"2025-01-06","arxiv_id":"2501.02785","repositories_listed":0,"syntology":null},{"url":null,"slug":"multi-modal-one-shot-federated-ensemble","title":"Multi-Modal One-Shot Federated Ensemble Learning for Medical Data with Vision Large Language Model","date":"2025-01-06","arxiv_id":"2501.03292","repositories_listed":0,"syntology":null},{"url":null,"slug":"region-of-interest-based-medical-image","title":"Region of Interest based Medical Image Compression","date":"2025-01-06","arxiv_id":"2501.02895","repositories_listed":0,"syntology":null},{"url":null,"slug":"tree-based-rag-agent-recommendation-system-a","title":"Tree-based RAG-Agent Recommendation System: A Case Study in Medical Test Data","date":"2025-01-06","arxiv_id":"2501.02727","repositories_listed":0,"syntology":null},{"url":null,"slug":"gaze-behavior-during-a-long-term-in-home","title":"Gaze Behavior During a Long-Term, In-Home, Social Robot Intervention for Children with ASD","date":"2025-01-05","arxiv_id":"2501.02583","repositories_listed":0,"syntology":null},{"url":null,"slug":"hengqin-ra-v1-advanced-large-language-model","title":"Hengqin-RA-v1: Advanced Large Language Model for Diagnosis and Treatment of Rheumatoid Arthritis with Dataset based Traditional Chinese Medicine","date":"2025-01-05","arxiv_id":"2501.02471","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-learning-driven-segmentation-of-ischemic","title":"Deep Learning-Driven Segmentation of Ischemic Stroke Lesions Using Multi-Channel MRI","date":"2025-01-04","arxiv_id":"2501.02287","repositories_listed":0,"syntology":null},{"url":null,"slug":"avtrustbench-assessing-and-enhancing","title":"AVTrustBench: Assessing and Enhancing Reliability and Robustness in Audio-Visual LLMs","date":"2025-01-03","arxiv_id":"2501.02135","repositories_listed":0,"syntology":null},{"url":null,"slug":"counterfactual-explanation-for-auto-encoder","title":"Counterfactual Explanation for Auto-Encoder Based Time-Series Anomaly Detection","date":"2025-01-03","arxiv_id":"2501.02069","repositories_listed":0,"syntology":null},{"url":null,"slug":"mocoll-agent-based-specific-and-general-model","title":"MoColl: Agent-Based Specific and General Model Collaboration for Image Captioning","date":"2025-01-03","arxiv_id":"2501.01834","repositories_listed":0,"syntology":null},{"url":null,"slug":"radhop-net-a-lightweight-radiomics-to-error","title":"RadHop-Net: A Lightweight Radiomics-to-Error Regression for False Positive Reduction In MRI Prostate Cancer Detection","date":"2025-01-03","arxiv_id":"2501.02066","repositories_listed":0,"syntology":null},{"url":null,"slug":"evidential-calibrated-uncertainty-guided","title":"Evidential Calibrated Uncertainty-Guided Interactive Segmentation paradigm for Ultrasound Images","date":"2025-01-02","arxiv_id":"2501.01072","repositories_listed":0,"syntology":null},{"url":null,"slug":"large-language-models-for-mental-health-1","title":"Large Language Models for Mental Health Diagnostic Assessments: Exploring The Potential of Large Language Models for Assisting with Mental Health Diagnostic Assessments -- The Depression and Anxiety Case","date":"2025-01-02","arxiv_id":"2501.01305","repositories_listed":0,"syntology":null},{"url":null,"slug":"machine-learning-based-differential-diagnosis","title":"Machine Learning-Based Differential Diagnosis of Parkinson's Disease Using Kinematic Feature Extraction and Selection","date":"2025-01-02","arxiv_id":"2501.02014","repositories_listed":0,"syntology":null},{"url":null,"slug":"ultrasound-lung-aeration-map-via-physics","title":"Ultrasound Lung Aeration Map via Physics-Aware Neural Operators","date":"2025-01-02","arxiv_id":"2501.01157","repositories_listed":0,"syntology":null},{"url":null,"slug":"vigil3d-a-linguistically-diverse-dataset-for","title":"ViGiL3D: A Linguistically Diverse Dataset for 3D Visual Grounding","date":"2025-01-02","arxiv_id":"2501.01366","repositories_listed":0,"syntology":null},{"url":null,"slug":"ddd-discriminative-difficulty-distance-for","title":"DDD: Discriminative Difficulty Distance for plant disease diagnosis","date":"2025-01-01","arxiv_id":"2501.00734","repositories_listed":0,"syntology":null},{"url":null,"slug":"multi-modal-medical-diagnosis-via-large-small","title":"Multi-modal Medical Diagnosis via Large-small Model Collaboration","date":"2025-01-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"oralxrays-9-towards-hospital-scale-panoramic","title":"OralXrays-9: Towards Hospital-Scale Panoramic X-ray Anomaly Detection via Personalized Multi-Object Query-Aware Mining","date":"2025-01-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"spatial457-a-diagnostic-benchmark-for-6d","title":"Spatial457: A Diagnostic Benchmark for 6D Spatial Reasoning of Large Mutimodal Models","date":"2025-01-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"svlta-benchmarking-vision-language-temporal","title":"SVLTA: Benchmarking Vision-Language Temporal Alignment via Synthetic Video Situation","date":"2025-01-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"addressing-challenges-in-data-quality-and","title":"Addressing Challenges in Data Quality and Model Generalization for Malaria Detection","date":"2024-12-31","arxiv_id":"2501.00464","repositories_listed":0,"syntology":null},{"url":null,"slug":"pan-infection-foundation-framework-enables","title":"Pan-infection Foundation Framework Enables Multiple Pathogen Prediction","date":"2024-12-31","arxiv_id":"2501.01462","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-data-centric-approach-to-detecting-and","title":"A Data-Centric Approach to Detecting and Mitigating Demographic Bias in Pediatric Mental Health Text: A Case Study in Anxiety Detection","date":"2024-12-30","arxiv_id":"2501.00129","repositories_listed":0,"syntology":null},{"url":null,"slug":"active-learning-with-variational-quantum","title":"Active Learning with Variational Quantum Circuits for Quantum Process Tomography","date":"2024-12-30","arxiv_id":"2412.20925","repositories_listed":0,"syntology":null},{"url":null,"slug":"advancing-parkinson-s-disease-progression","title":"Advancing Parkinson's Disease Progression Prediction: Comparing Long Short-Term Memory Networks and Kolmogorov-Arnold Networks","date":"2024-12-30","arxiv_id":"2412.20744","repositories_listed":0,"syntology":null},{"url":null,"slug":"residual-connection-networks-in-medical-image","title":"Residual Connection Networks in Medical Image Processing: Exploration of ResUnet++ Model Driven by Human Computer Interaction","date":"2024-12-30","arxiv_id":"2412.20709","repositories_listed":0,"syntology":null},{"url":null,"slug":"enhancing-cognitive-diagnosis-by-modeling","title":"Enhancing Cognitive Diagnosis by Modeling Learner Cognitive Structure State","date":"2024-12-27","arxiv_id":"2412.19759","repositories_listed":0,"syntology":null},{"url":null,"slug":"few-shot-metric-domain-adaptation-practical","title":"Few-shot Metric Domain Adaptation: Practical Learning Strategies for an Automated Plant Disease Diagnosis","date":"2024-12-25","arxiv_id":"2412.18859","repositories_listed":0,"syntology":null},{"url":null,"slug":"detection-and-forecasting-of-parkinson","title":"Detection and Forecasting of Parkinson Disease Progression from Speech Signal Features Using MultiLayer Perceptron and LSTM","date":"2024-12-24","arxiv_id":"2412.18248","repositories_listed":0,"syntology":null},{"url":null,"slug":"research-on-the-proximity-relationships-of","title":"Research on the Proximity Relationships of Psychosomatic Disease Knowledge Graph Modules Extracted by Large Language Models","date":"2024-12-24","arxiv_id":"2412.18419","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-multimodal-emotion-recognition-system","title":"A Multimodal Emotion Recognition System: Integrating Facial Expressions, Body Movement, Speech, and Spoken Language","date":"2024-12-23","arxiv_id":"2412.17907","repositories_listed":0,"syntology":null},{"url":null,"slug":"v-2-sfmlearner-learning-monocular-depth-and","title":"V$^2$-SfMLearner: Learning Monocular Depth and Ego-motion for Multimodal Wireless Capsule Endoscopy","date":"2024-12-23","arxiv_id":"2412.17595","repositories_listed":0,"syntology":null},{"url":null,"slug":"the-potential-of-convolutional-neural","title":"The Potential of Convolutional Neural Networks for Cancer Detection","date":"2024-12-22","arxiv_id":"2412.17155","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-generalizable-3d-diffusion-framework-for","title":"A Generalizable 3D Diffusion Framework for Low-Dose and Few-View Cardiac SPECT","date":"2024-12-21","arxiv_id":"2412.16573","repositories_listed":0,"syntology":null},{"url":null,"slug":"fairdd-enhancing-fairness-with-domain","title":"FairDD: Enhancing Fairness with domain-incremental learning in dermatological disease diagnosis","date":"2024-12-21","arxiv_id":"2412.16542","repositories_listed":0,"syntology":null},{"url":null,"slug":"multi-atlas-ensemble-graph-neural-network","title":"Multi-atlas Ensemble Graph Neural Network Model For Major Depressive Disorder Detection Using Functional MRI Data","date":"2024-12-21","arxiv_id":"2412.19833","repositories_listed":0,"syntology":null},{"url":null,"slug":"can-input-attributions-interpret-the","title":"Can Input Attributions Interpret the Inductive Reasoning Process Elicited in In-Context Learning?","date":"2024-12-20","arxiv_id":"2412.15628","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-learning-joint-extremes-of-metocean","title":"Deep learning joint extremes of metocean variables using the SPAR model","date":"2024-12-20","arxiv_id":"2412.15808","repositories_listed":0,"syntology":null},{"url":null,"slug":"fairread-re-fusing-demographic-attributes","title":"FairREAD: Re-fusing Demographic Attributes after Disentanglement for Fair Medical Image Classification","date":"2024-12-20","arxiv_id":"2412.16373","repositories_listed":0,"syntology":null},{"url":null,"slug":"accelerated-patient-specific-calibration-via","title":"Accelerated Patient-Specific Calibration via Differentiable Hemodynamics Simulations","date":"2024-12-19","arxiv_id":"2412.14572","repositories_listed":0,"syntology":null},{"url":null,"slug":"automated-root-cause-analysis-system-for","title":"Automated Root Cause Analysis System for Complex Data Products","date":"2024-12-19","arxiv_id":"2412.15374","repositories_listed":0,"syntology":null},{"url":null,"slug":"maria-a-multimodal-transformer-model-for","title":"MARIA: a Multimodal Transformer Model for Incomplete Healthcare Data","date":"2024-12-19","arxiv_id":"2412.14810","repositories_listed":0,"syntology":null},{"url":null,"slug":"constraint-based-model-in-multimodal-learning","title":"Constraint-Based Model in Multimodal Learning to Improve Ventricular Arrhythmia Prediction","date":"2024-12-18","arxiv_id":"2412.17840","repositories_listed":0,"syntology":null}],"record_sha256":"3fb257488db748ebe6b0c62071da3add6a497a32d6a8782ed409f28dc0db24e9","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}