Limbix (by BigHealth)
Evidence-based digital therapeutics for adolescent mental health and behavioral activation.
Clinical-grade dermatological assessment and lesion tracking powered by proprietary deep learning ensembles.
DermAI Scanner represents the 2026 frontier of clinical decision support systems (CDSS) specifically engineered for dermatological pathology. Utilizing a multi-stage Ensemble Convolutional Neural Network (ECNN) architecture, it processes high-resolution dermoscopic and macroscopic images to identify over 150 distinct skin conditions, ranging from benign melanocytic nevi to aggressive carcinomas. The platform's technical core is built on the ISIC (International Skin Imaging Collaboration) 2025 dataset, enhanced by synthetic data generation to minimize bias across diverse skin phototypes (Fitzpatrick scales I-VI). In the 2026 market, DermAI Scanner positions itself as an essential bridge between primary care and specialized dermatology, reducing unnecessary biopsies by an estimated 22% through its high specificity. The system operates on a low-latency edge-computing model for mobile devices while maintaining a HIPAA-compliant, cloud-based longitudinal tracking system for patient records. Its 2026 iteration includes advanced temporal analysis, allowing the AI to detect 'ugly duckling' lesions by comparing current scans against historical patient data via 3D body mapping tech.
Uses ARCore/ARKit to map lesions onto a 3D digital twin of the patient for precise spatial tracking.
Evidence-based digital therapeutics for adolescent mental health and behavioral activation.
Predictive clinical and operational intelligence to fight death and waste in healthcare.
Predictive medical data and clinical insights for streamlined enterprise underwriting.
The professional medical network for clinicians, providing HIPAA-compliant AI and telehealth solutions.
Verified feedback from the global deployment network.
Post queries, share implementation strategies, and help other users.
Generative Adversarial Networks (GANs) are used to balance the training set for rare pathologies and varied skin tones.
Optimized TensorFlow Lite models run locally on-device to minimize latency and improve data privacy.
Native support for Fast Healthcare Interoperability Resources for seamless data transfer to Epic and Cerner.
Algorithmic reconstruction of sub-epidermal structures from multi-spectral light data.
Real-time computer vision feedback to ensure the user maintains optimal distance, focus, and lighting.
Deep learning models predict the 6-month visual trajectory of a lesion based on historical change rates.
PCPs often lack specialized training to differentiate between benign and malignant lesions.
Registry Updated:2/7/2026
High readmission rates due to undetected surgical site infections.
Inconsistent manual measurement of lesion reduction in pharmaceutical trials.