AI solutions
for healthcare
Stay efficient in the wake of the pandemic and redefine the approach to diagnosing, treating, and communicating with patients by adopting artificial intelligence healthcare solutions Talk to our AI Developers
Faster Diagnosis. Better Treatment Outcomes. AI Lab combines the power of accelerated computing, AI, and machine learning to supercharge the entire drug development process, unlocking the potential to bring life-saving drugs to market faster. Get Started How it work? Artificial Intelligence in Decision Support Systems for Diagnosis in Medical Imaging Medical imaging offers essential information on patients’ medical condition, and clues to causes of their symptoms and diseases. Get Started How it work?

Advancing Medicine with AI-Powered Solutions

Disease Identification & Diagnosis

ML algorithms detect patterns associated with diseases and health conditions by studying thousands of healthcare records and other patient data.

01

Medical Imaging Diagnosis

Artificial intelligence can support radiologists and pathologists as they use medical imaging to diagnose a wide variety of conditions.

02

Robotic Surgery

ML can use real-time data, information to improve the accuracy of surgical robotic tools. The benefits include reduced human error, aid during more complex procedures and less invasive surgeries.

03

Genome Sequencing Analysis

Optimized for speed, accuracy, and scalability. Best Practices and is fully configurable, allowing users to choose which steps, parameter settings, and versions of the pipeline to run.

04

Smart Hospitals

Brings intelligent video analytics and conversational AI capabilities to healthcare, simplifying the development for automated body temperature screening, protective mask detection, and remote patient monitoring.

05

Diagnostic system from medical imaging

To meet the growing demand for care, medical technology leaders are turning to AI tools that can help radiation oncologists provide high-quality, individualized treatment faster.

Forecasting system on pharmacological reactions

Adverse drug reactions (ADRs) are an important concern in the medication process and can pose a substantial economic burden for patients and hospitals. Because of the limitations of clinical trials, it is difficult to identify all possible ADRs of a drug before it is marketed. We developed a new model based on data mining technology to predict potential ADRs based on available drug data.

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Optimization for Healthcare Insurance companies

Insurers are using artificial intelligence and machine learning to review medical records, optimize care for chronic conditions, identify risk.

Payers manage risk

Insurers are using artificial intelligence and machine learning to review medical records, optimize care for chronic conditions, identify risk.

AI to optimize health

AI and machine learning move from a custom and reactive approach to more standardized and proactive management of patient care.

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