SOTAVerified

Medical Diagnosis

Medical Diagnosis is the process of identifying the disease a patient is affected by, based on the assessment of specific risk factors, signs, symptoms and results of exams.

Source: A probabilistic network for the diagnosis of acute cardiopulmonary diseases

Papers

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Showing 376–400 of 714 papers

TitleStatusHype
Revealing Unfair Models by Mining Interpretable Evidence—0
RFC-Net: Learning High Resolution Global Features for Medical Image Segmentation on a Computational Budget—0
RF Sensing for Continuous Monitoring of Human Activities for Home Consumer Applications—0
RGB-D image-based Object Detection: from Traditional Methods to Deep Learning Techniques—0
RJUA-MedDQA: A Multimodal Benchmark for Medical Document Question Answering and Clinical Reasoning—0
Robust Collaborative Learning of Patch-level and Image-level Annotations for Diabetic Retinopathy Grading from Fundus Image—0
Robustness of an Artificial Intelligence Solution for Diagnosis of Normal Chest X-Rays—0
SAM-LAD: Segment Anything Model Meets Zero-Shot Logic Anomaly Detection—0
Sample Complexity of Deep Active Learning—0
Sample Efficient Learning of Image-Based Diagnostic Classifiers Using Probabilistic Labels—0
Sampling for Deep Learning Model Diagnosis (Technical Report)—0
Security and Privacy Challenges in Deep Learning Models—0
Segmentation of large images based on super-pixels and community detection in graphs—0
SeismoFlow -- Data augmentation for the class imbalance problem—0
Selecting a classification performance measure: matching the measure to the problem—0
Selective classification using a robust meta-learning approach—0
Selective Ensembles for Consistent Predictions—0
Self-Supervised Learning Featuring Small-Scale Image Dataset for Treatable Retinal Diseases Classification—0
Self-Supervised Masking for Unsupervised Anomaly Detection and Localization—0
Self-supervised Model Based on Masked Autoencoders Advance CT Scans Classification—0
Semantic Decomposition Improves Learning of Large Language Models on EHR Data—0
Semantic denoising autoencoders for retinal optical coherence tomography—0
Semantic Similarity To Improve Question Understanding in a Virtual Patient—0
Semi-Supervised Deep Learning Using Improved Unsupervised Discriminant Projection—0
Sequential-Scanning Dual-Energy CT Imaging Using High Temporal Resolution Image Reconstruction and Error-Compensated Material Basis Image Generation—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1DenseNet-161Average Precision0.74—Unverified