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 401–450 of 714 papers

TitleStatusHype
Learning to Predict Error for MRI Reconstruction—0
Single-step Adversarial training with Dropout Scheduling—0
SkelMamba: A State Space Model for Efficient Skeleton Action Recognition of Neurological Disorders—0
Slice-level Detection of Intracranial Hemorrhage on CT Using Deep Descriptors of Adjacent Slices—0
Smart machines and the SP theory of intelligence—0
SMFusion: Semantic-Preserving Fusion of Multimodal Medical Images for Enhanced Clinical Diagnosis—0
Sparse Variational Bayesian Approximations for Nonlinear Inverse Problems: applications in nonlinear elastography—0
Sparsity- and Hybridity-Inspired Visual Parameter-Efficient Fine-Tuning for Medical Diagnosis—0
Spatio-spectral classification of hyperspectral images for brain cancer detection during surgical operations—0
Spatio-Temporal Structure Consistency for Semi-supervised Medical Image Classification—0
SpecReX: Explainable AI for Raman Spectroscopy—0
Specular reflections removal in colposcopic images based on neural networks: Supervised training with no ground truth previous knowledge—0
SpikingJET: Enhancing Fault Injection for Fully and Convolutional Spiking Neural Networks—0
SpineOne: A One-Stage Detection Framework for Degenerative Discs and Vertebrae—0
Stabilized Medical Attacks—0
Stabilizing Adversarially Learned One-Class Novelty Detection Using Pseudo Anomalies—0
Stable Vision Concept Transformers for Medical Diagnosis—0
Stacked Autoencoders for Medical Image Search—0
Statistical reproducibility of meta-analysis research claims for medical mask use in community settings to prevent COVID infection—0
Statistical Test for Anomaly Detections by Variational Auto-Encoders—0
Stochastic Sequential Neural Networks with Structured Inference—0
StrokeSave: A Novel, High-Performance Mobile Application for Stroke Diagnosis using Deep Learning and Computer Vision—0
StudyFormer : Attention-Based and Dynamic Multi View Classifier for X-ray images—0
Subtype-aware Unsupervised Domain Adaptation for Medical Diagnosis—0
A Two-step Surface-based 3D Deep Learning Pipeline for Segmentation of Intracranial Aneurysms—0
TAD: Trigger Approximation based Black-box Trojan Detection for AI—0
Taming Stable Diffusion for Computed Tomography Blind Super-Resolution—0
TEAM PILOT -- Learned Feasible Extendable Set of Dynamic MRI Acquisition Trajectories—0
Technical Challenges for Training Fair Neural Networks—0
Testing Machine Translation via Referential Transparency—0
Test Set Selection using Active Information Acquisition for Predictive Models—0
TESTSGD: Interpretable Testing of Neural Networks Against Subtle Group Discrimination—0
Text Classification using Graph Convolutional Networks: A Comprehensive Survey—0
Texture-Aware StarGAN for CT data harmonisation—0
The Continuity of Images by Transmission Imaging Revisited—0
The Reliability of LLMs for Medical Diagnosis: An Examination of Consistency, Manipulation, and Contextual Awareness—0
The Return of Pseudosciences in Artificial Intelligence: Have Machine Learning and Deep Learning Forgotten Lessons from Statistics and History?—0
The Role of Explainable AI in Revolutionizing Human Health Monitoring: A Review—0
The SP Theory of Intelligence as a Foundation for the Development of a General, Human-Level Thinking Machine—0
The SP theory of intelligence: benefits and applications—0
Two-stage deep learning framework for the restoration of incomplete-ring PET images—0
The Utility of Abstaining in Binary Classification—0
The Value of Context: Human versus Black Box Evaluators—0
Tiny Deep Ensemble: Uncertainty Estimation in Edge AI Accelerators via Ensembling Normalization Layers with Shared Weights—0
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
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Benchmark Results

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