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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 376–400 of 714 papers

TitleStatusHype
Tipping the Scales: A Corpus-Based Reconstruction of Adjective Scales in the McGill Pain Questionnaire—0
Toward a Fairness-Aware Scoring System for Algorithmic Decision-Making—0
Towards Automatic Evaluation for LLMs' Clinical Capabilities: Metric, Data, and Algorithm—0
Towards CT-quality Ultrasound Imaging using Deep Learning—0
Towards new forms of particle sensing and manipulation and 3D imaging on a smartphone for healthcare applications—0
Towards Practical Verification of Machine Learning: The Case of Computer Vision Systems—0
Towards Reducing Aleatoric Uncertainty for Medical Imaging Tasks—0
Towards Understanding The Calibration Benefits of Sharpness-Aware Minimization—0
Uncertainty-aware abstention in medical diagnosis based on medical texts—0
Uncertainty-Aware Deep Learning for Automated Skin Cancer Classification: A Comprehensive Evaluation—0
Uncertainty Estimation and Out-of-Distribution Detection for Counterfactual Explanations: Pitfalls and Solutions—0
Uncertainty-Estimation with Normalized Logits for Out-of-Distribution Detection—0
Uncertainty Quantification in Machine Learning Based Segmentation: A Post-Hoc Approach for Left Ventricle Volume Estimation in MRI—0
Uncertainty Quantification of Deep Learning for Spatiotemporal Data: Challenges and Opportunities—0
Understanding and Enhancing Robustness of Concept-based Models—0
Understanding differences in applying DETR to natural and medical images—0
Unfolding Tensors to Identify the Graph in Discrete Latent Bipartite Graphical Models—0
Unimodal-uniform Constrained Wasserstein Training for Medical Diagnosis—0
Unlocking the Potential of ChatGPT: A Comprehensive Exploration of its Applications, Advantages, Limitations, and Future Directions in Natural Language Processing—0
Unsupervised Deep Digital Staining For Microscopic Cell Images Via Knowledge Distillation—0
Unsupervised Learning of Noisy-Or Bayesian Networks—0
Unsupervised Online Feature Selection for Cost-Sensitive Medical Diagnosis—0
Unsupervised Temperature Scaling: An Unsupervised Post-Processing Calibration Method of Deep Networks—0
Using Belief Functions for Uncertainty Management and Knowledge Acquisition: An Expert Application—0
Using Convolutional Neural Networks for fault analysis and alleviation in accelerator systems—0
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Benchmark Results

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