Healthcare & Life Sciences

Accelerated AI Solutions for
Better Healthcare Outcomes
Solution brief

Healthcare & Life Sciences

Accelerated AI Solutions for
Better Healthcare Outcomes

AI Advances Patient Care

Healthcare and life sciences organizations are unique in that they address urgent life and death challenges every day. The high stakes, combined with critical regulatory and privacy concerns, can make it difficult to focus on crucial innovation projects.

To enhance patient experiences and outcomes while accelerating competitive innovation, healthcare and life sciences organizations must be able to efficiently implement AI solutions that advance personalized medicine and improve the patient journey.

Offload Complexity, Innovate Competitively

Dataflow-as-a-ServiceTM augments your organization’s AI expertise by providing a comprehensive platform, services, and models that enable healthcare and life sciences organizations to develop and deploy state-of-the-art AI solutions without the time and expense of building complex AI architectures and hiring teams of machine learning experts.

Slow and expensive, drug discovery requires an average of ten years and nearly $3 billion to complete, from idea to prescription. To get life-saving drugs to market faster, the industry is working to integrate AI at every stage from research, to clinical trials, and beyond. Drug companies are building massive AI-driven knowledge graphs that reveal critical connections between proteins, molecules, and pathways—empowering them to improve analysis and make better, faster decisions about the viability of drug targets. Genomics data, which is growing at astronomical rates, is driving a revolution in personalized medicine but requires levels of AI compute power that go beyond the limitations of traditional technologies.

Many computer vision use cases in healthcare and life sciences, particularly those around cancer research and diagnosis, rely on how accurately a high-resolution image can be analyzed. The key to more accurate screening and diagnostics across a number of healthcare and pharma applications is the ability to use true-resolution images to train deep learning models without long run times, tiling, and down-sampling — bottlenecks and workarounds necessitated by conventional AI systems that also sacrifice accuracy. Next-generation AI technology is needed to drive real breakthroughs in medical imaging and improve patient outcomes.

COVID-19 advanced telehealth five years in a matter of months. It also exposed a need to make every aspect of telehealth smarter and more personalized. Post-pandemic, AI innovations in telehealth will continue to make virtual care a more mainstream, cost-effective part of the ecosystem. From conversational AI to accurate recommendation models that improve the patient journey—advanced AI models are driving better patient experiences. Accelerating delivery of virtual care, such as doctor matching, symptom checking, and “next-best” action recommendations, AI will be increasingly utilized to help patients navigate the continuum of care while personalizing and improving treatment.

Use Cases

Drug Discovery and Genomics

Slow and expensive, drug discovery requires an average of ten years and nearly $3 billion to complete, from idea to prescription. To get life-saving drugs to market faster, the industry is working to integrate AI at every stage from research, to clinical trials, and beyond. Drug companies are building massive AI-driven knowledge graphs that reveal critical connections between proteins, molecules, and pathways—empowering them to improve analysis and make better, faster decisions about the viability of drug targets. Genomics data, which is growing at astronomical rates, is driving a revolution in personalized medicine but requires levels of AI compute power that go beyond the limitations of traditional technologies.

Medical Imaging

Many computer vision use cases in healthcare and life sciences, particularly those around cancer research and diagnosis, rely on how accurately a high-resolution image can be analyzed. The key to more accurate screening and diagnostics across a number of healthcare and pharma applications is the ability to use true-resolution images to train deep learning models without long run times, tiling, and down-sampling — bottlenecks and workarounds necessitated by conventional AI systems that also sacrifice accuracy. Next-generation AI technology is needed to drive real breakthroughs in medical imaging and improve patient outcomes.

Telehealth

COVID-19 advanced telehealth five years in a matter of months. It also exposed a need to make every aspect of telehealth smarter and more personalized. Post-pandemic, AI innovations in telehealth will continue to make virtual care a more mainstream, cost-effective part of the ecosystem. From conversational AI to accurate recommendation models that improve the patient journey—advanced AI models are driving better patient experiences. Accelerating delivery of virtual care, such as doctor matching, symptom checking, and “next-best” action recommendations, AI will be increasingly utilized to help patients navigate the continuum of care while personalizing and improving treatment.

Accelerated AI Services for Healthcare & Life Sciences

SambaNova enables healthcare and life sciences organizations to deliver AI innovations that drive patient engagement, clinical breakthroughs, and better patient outcomes.

DATAFLOW-AS-A-SERVICE
FOR LANGUAGE

Achieve breakthrough efficiency in NLP while you free up your machine learning talent to focus on higher-value initiatives.

DATAFLOW-AS-A-SERVICE
FOR VISION

In machine learning image processing and analysis—resolution is everything. Unlock the full advantage of your high-resolution images.

DATAFLOW-AS-A-SERVICE
FOR RECOMMENDATION

Improve the accuracy of your predictions to deliver more personalized, meaningful information and content to your end-users.

Learn how SambaNova can help your organization leverage AI to improve patient engagement and outcomes.

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