Models

Discover and deploy state-of-the-art disease detection models

Stanford

BrainTumorNet-v2

Stanford Medical AI Lab

Featured

Advanced brain tumor detection and segmentation model with 99.8% accuracy on validation dataset.

4.9 (2.3k reviews) • 50k+ downloads
PyTorch GPU Optimized
Mayo Clinic

PathologyVision-Large

Mayo Clinic AI Research

New

State-of-the-art digital pathology analysis model for cancer detection and classification.

4.8 (1.8k reviews) • 35k+ downloads
TensorFlow FDA Approved
MIT

GenomeDetect-XL

MIT BioAI Lab

Large-scale genomic variant detection model for early disease prediction.

4.7 (950 reviews) • 20k+ downloads
JAX Research
DeepMind

ChestXpert-3D

DeepMind Health

Advanced chest X-ray analysis model with 3D reconstruction capabilities.

4.9 (3.1k reviews) • 75k+ downloads
PyTorch CE Marked
Harvard

DermaDetect-Pro

Harvard Medical School

Skin disease detection and classification model with mobile deployment support.

4.8 (1.5k reviews) • 40k+ downloads
TensorFlow Lite Mobile
Oxford

CardioNet-RT

Oxford Medical AI

Real-time cardiovascular disease detection from ECG signals.

4.7 (2.8k reviews) • 45k+ downloads
ONNX Real-time
Johns Hopkins

NeuroSeg-Pro

Johns Hopkins Neurology

FDA Cleared

Advanced neural segmentation model for stroke detection and tumor boundary analysis with real-time 3D reconstruction.

4.9 (1.2k reviews) • 30k+ downloads
TensorFlow CUDA Optimized
Sloan Kettering

OncoPredictXL

Memorial Sloan Kettering

Clinical Trial

Multi-modal cancer prediction model integrating imaging, genomics, and clinical data for early-stage detection.

4.8 (980 reviews) • 15k+ downloads
PyTorch Multi-Modal
Cleveland Clinic

CardioRisk-AI

Cleveland Clinic

CE Marked

Cardiovascular risk prediction model using ECG, imaging, and longitudinal patient data with 5-year outcome forecasting.

4.9 (2.5k reviews) • 40k+ downloads
Time Series Validated
{ name: "BrainAge-Net", institution: "UCL Neuroscience", institutionImage: "https://images.unsplash.com/photo-1584362917165-526a968579e8?auto=format&fit=crop&w=100&h=100", description: "Brain age prediction and neurodegeneration analysis using structural MRI scans.", rating: "4.7", reviews: "890", downloads: "22k", status: "Verified", statusClass: "bg-blue-100 text-blue-800", category: "neurology", tags: [ { name: "Deep Learning", class: "bg-purple-100 text-purple-800" }, { name: "MRI", class: "bg-green-100 text-green-800" } ] }, { name: "RadiologyGPT", institution: "MIT Medical", institutionImage: "https://images.unsplash.com/photo-1576670159805-381a0b226e22?auto=format&fit=crop&w=100&h=100", description: "Advanced radiology report generation with multi-modal understanding of medical imaging.", rating: "4.8", reviews: "2.1k", downloads: "35k", status: "FDA Cleared", statusClass: "bg-green-100 text-green-800", category: "radiology", tags: [ { name: "Transformer", class: "bg-pink-100 text-pink-800" }, { name: "Multi-Modal", class: "bg-blue-100 text-blue-800" } ] }, { name: "CardiacMRI-Seg", institution: "Oxford Cardiology", institutionImage: "https://images.unsplash.com/photo-1551076805-e1869033e561?auto=format&fit=crop&w=100&h=100", description: "Cardiac MRI segmentation with 4D flow analysis and ejection fraction calculation.", rating: "4.9", reviews: "1.8k", downloads: "28k", status: "CE Marked", statusClass: "bg-green-100 text-green-800", category: "cardiology", tags: [ { name: "4D Analysis", class: "bg-indigo-100 text-indigo-800" }, { name: "Real-time", class: "bg-yellow-100 text-yellow-800" } ] }, { name: "PathologyVision", institution: "UCSF Pathology", institutionImage: "https://images.unsplash.com/photo-1576670159805-381a0b226e22?auto=format&fit=crop&w=100&h=100", description: "Digital pathology analysis with multi-stain support and cellular classification.", rating: "4.7", reviews: "950", downloads: "19k", status: "FDA Cleared", statusClass: "bg-green-100 text-green-800", category: "pathology", tags: [ { name: "Vision", class: "bg-blue-100 text-blue-800" }, { name: "Classification", class: "bg-purple-100 text-purple-800" } ] }, { name: "GeneExpressionNet", institution: "Harvard Medical", institutionImage: "https://images.unsplash.com/photo-1532187863486-abf9dbad1b69?auto=format&fit=crop&w=100&h=100", description: "Gene expression analysis and pathway prediction using transformer architecture.", rating: "4.8", reviews: "780", downloads: "15k", status: "Verified", statusClass: "bg-blue-100 text-blue-800", category: "genomics", tags: [ { name: "RNA-Seq", class: "bg-green-100 text-green-800" }, { name: "Transformer", class: "bg-pink-100 text-pink-800" } ] }, { name: "ClinicalNLP", institution: "Stanford NLP", institutionImage: "https://images.unsplash.com/photo-1532187863486-abf9dbad1b69?auto=format&fit=crop&w=100&h=100", description: "Clinical note analysis and structured data extraction with medical ontology mapping.", rating: "4.6", reviews: "650", downloads: "12k", status: "Validated", statusClass: "bg-green-100 text-green-800", category: "clinical", tags: [ { name: "NLP", class: "bg-indigo-100 text-indigo-800" }, { name: "BERT", class: "bg-yellow-100 text-yellow-800" } ] }, { name: "TumorSegment3D", institution: "MD Anderson", institutionImage: "https://images.unsplash.com/photo-1576671081837-49b1a991dd54?auto=format&fit=crop&w=100&h=100", description: "3D tumor segmentation and volume analysis for treatment planning.", rating: "4.9", reviews: "1.5k", downloads: "25k", status: "FDA Cleared", statusClass: "bg-green-100 text-green-800", category: "oncology", tags: [ { name: "3D Analysis", class: "bg-blue-100 text-blue-800" }, { name: "GPU Optimized", class: "bg-purple-100 text-purple-800" } ] }, { name: "StrokeDetect", institution: "Mass General", institutionImage: "https://images.unsplash.com/photo-1584362917165-526a968579e8?auto=format&fit=crop&w=100&h=100", description: "Real-time stroke detection and classification from CT perfusion imaging.", rating: "4.8", reviews: "2.2k", downloads: "38k", status: "FDA Cleared", statusClass: "bg-green-100 text-green-800", category: "neurology", tags: [ { name: "Real-time", class: "bg-yellow-100 text-yellow-800" }, { name: "CT", class: "bg-blue-100 text-blue-800" } ] }, { name: "ChestXRay-AI", institution: "NIH Clinical Center", institutionImage: "https://images.unsplash.com/photo-1576670159805-381a0b226e22?auto=format&fit=crop&w=100&h=100", description: "Comprehensive chest X-ray analysis with 14 pathology classifications.", rating: "4.7", reviews: "3.1k", downloads: "45k", status: "FDA Cleared", statusClass: "bg-green-100 text-green-800", category: "radiology", tags: [ { name: "X-Ray", class: "bg-indigo-100 text-indigo-800" }, { name: "Multi-label", class: "bg-red-100 text-red-800" } ] }, { name: "AFib-Detect", institution: "Mayo Cardiology", institutionImage: "https://images.unsplash.com/photo-1551076805-e1869033e561?auto=format&fit=crop&w=100&h=100", description: "Atrial fibrillation detection and risk stratification from ECG signals.", rating: "4.9", reviews: "2.8k", downloads: "42k", status: "CE Marked", statusClass: "bg-green-100 text-green-800", category: "cardiology", tags: [ { name: "ECG", class: "bg-yellow-100 text-yellow-800" }, { name: "Real-time", class: "bg-blue-100 text-blue-800" } ] }