Our AI solutions enhance patient monitoring, predict disease risks, and automate diagnostics—helping medical professionals make informed decisions faster.
Chest X-Ray Disease Classifier
- AI model that classifies conditions like pneumonia or TB from X-ray images.
- Trained with medical datasets using CNN and attention mechanisms.
- Highlights affected areas for doctor verification.
- Used in rural clinics for second-opinion diagnostics.
- Integrates with PACS and mobile diagnostic tools.
Lung Cancer Detection from CT Scans
- CNN-based system to detect nodules and classify lung cancer stages.
- Includes heatmaps for explainability.
- Speeds up diagnosis and improves rural access.
Skin Cancer Detection
- Classifies melanoma, carcinoma, and benign lesions.
- Uses ISIC dataset and ResNet/Attention hybrid models.
- Includes severity score and treatment suggestions.
- Enhances early screening accuracy.
Brain Tumor Segmentation from MRI
- UNet model for multi-class segmentation of glioma, meningioma, pituitary tumors.
- Works with contrast MRI scans.
- Assists neurosurgeons in planning and outcome assessment.
- Deployed in diagnostic workstations.
Malnutrition Detection via Facial Analysis
- AI model trained on facial features to detect signs of severe malnutrition.
- Used in pediatric clinics and relief zones.
- Classifies severity levels and generates case profiles.
- Improves triaging in under-resourced areas.
Heart Disease Prediction from ECG
- CNN + LSTM model trained on 12-lead ECG signals.
- Detects arrhythmia, AFib, and early MI signs.
- Used in remote patient monitoring systems.
- Auto-generates structured medical reports.
Heart Disease Prediction from Patient Records
- AI model predicts heart disease risk based on clinical health parameters.
- Enables early intervention by flagging high-risk individuals.
- Trained on large-scale anonymized patient data.
- Boosts preventative care in cardiology.
- Useful in telehealth platforms and wellness apps.
Retinal Vessel Segmentation for Diabetic Retinopathy
- Segments blood vessels in retina scans to assess diabetic eye damage.
- Supports early-stage detection before vision loss occurs.
- Highlights vessel abnormalities and leakage patterns.
- Used in teleophthalmology and diabetic care clinics.
- Improves large-scale eye screening efficiency.
Dental Caries and Cavity Detection
- AI-powered dental X-ray analyzer for automatic cavity detection.
- Trained on thousands of panoramic dental radiographs.
- Used in dental chains for pre-screening.
- Classifies severity and suggests treatment action.
- Streamlines appointment planning and reduces human error.
Clinical Grade Vital Signs Monitor
- Wearable device for continuous patient monitoring using AI-enhanced sensors.
- Tracks pulse, SpO2, breath rate, and blood pressure in 20 seconds.
- Uses AI to filter noise and adapt to individual baselines.
- Clinical-grade accuracy with real-time dashboard and alerting system.
- Used in remote patient monitoring, hospitals, and wellness programs.
Cervical Cancer Prediction from Pap Smear Images
- AI model trained to detect cancerous and pre-cancerous cervical cells from microscope images.
- Helps in early detection and reduces human diagnostic errors.
- Built using labeled cytology image datasets.
- Assists gynecologists in automating screenings.
- Ideal for women’s clinics and mobile health programs.
Breast Cancer Histopathology Classification
- Classifies breast tissue samples into benign or malignant using deep learning.
- Utilizes histopathology images to identify cancer presence at early stages.
- Achieves high diagnostic accuracy by analyzing pixel patterns.
- Enables second-opinion diagnostics for oncologists.
- Perfect for labs, research centers, and pathology chains.
Diabetic Foot Ulcer Recognition
- Automatically identifies ulcers in diabetic foot images for risk evaluation.
- Helps prevent amputations by enabling timely intervention.
- Trained on large sets of foot wound photographs.
- Supports remote health workers and mobile screening.
- Essential in chronic care management programs.
Liver Tumor Segmentation from CT
- AI system segments liver tumors in CT scans for surgical planning.
- Differentiates tumor from liver tissues with high precision.
- Supports radiology teams in preoperative assessment.
- Improves treatment planning and reduces annotation time.
- Used in oncology imaging workflows.
Bone Fracture Detection in X-rays
- Detects fractures in wrist, elbow, and knee bones using X-ray images.
- Accelerates emergency diagnosis in trauma care.
- Supports radiologists by flagging fracture zones.
- Enables faster triaging and reduced diagnostic errors.
- Ideal for hospitals, mobile X-ray units, and urgent care.
Knee Osteoarthritis Detection from Radiographs
- Detects signs of osteoarthritis and grades severity from X-ray images.
- Identifies joint space narrowing and bony changes.
- Reduces manual variability in physician diagnosis.
- Helps with monitoring disease progression over time.
- Deployed in orthopedic care and digital health platforms.
Pneumonia Detection from Chest X-rays
- Detects signs of pneumonia in pediatric and adult chest X-rays.
- Provides AI-based triage support for healthcare professionals.
- Used in busy hospitals and low-resource diagnostic centers.
- Reduces diagnostic burden on radiologists.
- Vital for pandemic response and emergency care.
COVID-19 Detection from CT Scans
- Identifies COVID-19-related lung patterns from chest CT images.
- Used to triage and manage suspected COVID-19 cases.
- Provides fast AI feedback for overloaded radiology teams.
- Improves early detection and patient prioritization.
- Deployed during health crises and hospital surges.
Medical Waste Detection & Classification
- Detects and classifies biomedical waste into predefined categories.
- Enables compliance with environmental and disposal standards.
- Supports real-time sorting in hospitals and waste plants.
- Reduces contamination and improper disposal risks.
- Used by healthcare providers and sanitation authorities.
ICU Patient Monitoring with AI Alerts
- Predicts deterioration in ICU patients using clinical data patterns.
- Generates alerts for sepsis, cardiac events, or respiratory failure.
- Supports proactive monitoring with electronic medical records.
- Reduces critical event response time.
- Ideal for modern smart ICUs and hospital systems.
Post-Surgery Wound Infection Analysis
- Analyzes wound photos to detect signs of infection post-surgery.
- Tracks healing progress and flags abnormalities.
- Reduces the need for in-person follow-ups.
- Ideal for remote recovery monitoring and nursing support.
- Helps surgeons take timely corrective actions.
Scoliosis Detection from Spine Scans
- Detects abnormal spine curvatures and scoliosis severity.
- Estimates Cobb angles using spinal X-ray images.
- Used in early screening programs in schools and clinics.
- Supports orthopedic diagnosis and brace treatment planning.
- Enables digital record-keeping for spine evaluations.
Thyroid Nodule Classification from Ultrasound
- Classifies thyroid nodules as benign or malignant from ultrasound scans.
- Guides decisions on biopsy or active monitoring.
- Reduces unnecessary procedures using AI interpretation.
- Improves consistency in endocrinology clinics.
- Integrates with portable ultrasound devices.
MRI-based Schizophrenia and Dementia Risk Predictor
- Analyzes brain MRI scans to identify cognitive disorders.
- Flags atrophy or anomalies linked to dementia or schizophrenia.
- Used in clinical research and mental health diagnosis.
- Supports early intervention for at-risk patients.
- Integrated into neuroimaging analysis workflows.
Smart Stethoscope with AI Auscultation Analysis
- AI-enhanced audio analysis for heart and lung sounds.
- Detects murmurs, wheezes, and rhythm anomalies.
- Integrated with digital stethoscopes for doctors and paramedics.
- Supports remote patient care in telemedicine setups.
- Improves access to diagnostics in rural clinics.
Neonatal Jaundice Detection from Skin Color
- Computer vision model estimates bilirubin levels via baby skin tone.
- Non-invasive, fast screening for neonatal jaundice.
- Deployed in mobile health kits and rural delivery units.
- Reduces reliance on blood tests in remote areas.
- Promotes early treatment in newborn care programs.
Blood Cell Classification for Anemia/Malaria
- Classifies red and white blood cells to detect anemia or malaria.
- Analyzes microscope blood smear images using deep learning.
- Used in labs and portable diagnostic units.
- Assists in mass screenings and field clinics.
- Speeds up diagnosis and improves accuracy in critical care.
DNA Sequence Classifier for Disease Detection
- AI analyzes DNA sequences to identify disease-linked gene expressions.
- Supports early genetic screening and personalized medicine.
- Utilizes RNA sequencing datasets and feature engineering.
- Assists bioinformatics labs and research units.
- Promotes genomic diagnostics and therapy design.
Protein Structure Function Predictor
- AI predicts protein folding patterns and biological functions.
- Aids pharmaceutical companies in drug target discovery.
- Accelerates biomedical research and compound screening.
- Applies deep learning to protein sequencing data.
- Used in biotech R&D and molecular biology labs.
Molecular Property Prediction for Drug Discovery
- Machine learning predicts activity and toxicity of molecules.
- Streamlines early-stage pharmaceutical research.
- Reduces the cost of compound screening.
- Supports virtual lab environments.
- Enables faster drug development pipelines.
Adverse Drug Reaction Prediction from Patient Reviews
- Natural language processing flags drug side effects from real-world reviews.
- Improves post-marketing surveillance of medications.
- Assists pharmaceutical companies in identifying safety risks.
- Supports regulatory compliance.
- Deployable as a pharma feedback intelligence tool.
Drug-Target Interaction Prediction
- Deep learning identifies how drugs bind to biological targets.
- Speeds up new drug candidate discovery.
- Uses chemical and protein features for interaction mapping.
- Enhances precision in computational drug screening.
- Used by pharmaceutical research and biotech startups.
Parkinson’s Disease Prediction Using Voice Analysis
- AI analyzes voice recordings to detect signs of Parkinson’s.
- Detects speech variations linked to neurological decline.
- Supports early screening and remote assessments.
- Trained on patient audio datasets.
- Used in neuro AI diagnostics and mobile health apps.