Healthcare Data Management and Analysis Using Artificial Intelligence

 

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Mining clinical data to provide better and faster health services - Big Data analytics.

Provide physicians with evidence-based treatment options by analyzing the context and meaning of structured and unstructured data in clinical records.

Triaging application to find out patients who need urgent treatment using only the answers to a few questions by the patient or an accompanying person.

Monitoring, maintaining, analyzing and reporting data from wearable health trackers and sensors.

Integration of Artificial Intelligence (AI) with Electronic Medical Records (EMR) to create self learning and individualized Clinical Decision Support Systems.

 

Artificial Intelligence in Clinical Imaging

 

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What have we achieved with AI in Clinical Imaging?

 

MRI

Classification of MRI Brain images into abnormal and normal, as good as Radiologists. We are working on individual disease classification to create a complete diagnostic system. This is expected to help Radiologists manage heavy workload.

Volume calculation of hippocampus and cardiac ventricles from MRI images.

Classification of normal and abnormal inter-vertebral discs, as good as Radiologists. Working on detailed description of discal abnormalities.

Classification of normal and torn anterior cruciate ligament (knee), as good as Radiologists

 

CT

Detection of intracranial hemorrhage on CT Brain, as good as Radiologists.

Classification of lung nodules into benign and malignant, better than Radiologists.

 

X-rays

Classification of health check-up x-rays as normal and abnormal, as good as Radiologists.

Detection of pulmonary tuberculosis and pneumothorax on chest x-rays, as good as Radiologists.

Detection of bone fracture, better than Radiologists.

Bone age calculation from hand x-ray, better than Radiologists.

 

Ultrasound (US)

Classification of thyroid ultrasound into normal and abnormal, and further classification of diseases on abnormal scans, as good as Radiologists.

Classification of ocular (eye) ultrasound into normal and abnormal, and further classification of diseases on abnormal scans, as good as Radiologists.

 

Please check this page often for updates.

We are working on creating modality/body area specific complete diagnostic systems. This is expected to help Radiologists manage heavy workload and reduce error rates especially in the night.

 

AI-powered Custom Chatbots for the Healthcare Industry

 

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We develop state of the art AI-powered custom chatbots for use in various aspects of the healthcare industry, like treatment follow-up, appointment scheduling, payment processing, advertisements, reminders, HR, customer support, sales and more.

Our chatbots use latest technology to automate responses and use text, photos, voice and video.

Customers can be engaged through multiple channels like WhatsApp, Facebook Messenger, Twitter, Telegram, WeChat and more.

Hybrid chatbots use both humans and bots and humans can take over the conversation any time.

Collected data can be used for deeper analysis and reporting.

Artificial Intelligence in Health and Fitness

 

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Developing Artificial Intelligence (AI) powered applications to:

 

Regularly monitor, analyze and report user biometrics, activity, and sleep to ensure optimal fitness and give appropriate recommendations.

Regularly monitor, analyze and report user diet/nutrition to ensure optimal health and give appropriate recommendations.

Regularly monitor, analyze and report user exercise patterns to ensure optimal fitness and give appropriate recommendations.

Analyze genomic data to inform persons about their genetic risks and susceptibilities.

 

Artificial Intelligence in Drug Discovery

 

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We are experimenting with:


Using Artificial Intelligence (AI) to develop better diagnostics or biomarkers, identify drug targets and to design new drugs.
Finding better algorithms to develop drugs more quickly, and at a lesser cost.
Using AI to quickly find new uses for existing drugs or late-stage drug candidates.