Machine Learning for Healthcare & Life Sciences

Make sense of scientific and health data at scale

AWS machine learning empowers healthcare and life science organizations to make sense of their health data with purpose-built health AI services and the most comprehensive machine learning platform. Facing a robust set of challenges from the rising cost of healthcare to physician burnout to the inconsistent, complex nature of health data, healthcare and life science organizations are adopting machine learning to accelerate the pace of innovation and improve efficiency. AWS delivers unmatched reliability, security, and data privacy. With AWS machine learning, healthcare providers, payers, pharmaceutical companies, startups, ISVs and IT vendors are improving and accelerating diagnosis, managing population health, enabling drug discovery, and modernizing care infrastructure at a global scale.

Making sense of health data with AWS machine learning (3:19)

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Learn how to drive better patient and business outcomes with machine learning.

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Benefits

Make sense of health data

Understand and extract meaningful medical information from raw, disparate health data with advanced analytics and machine learning capabilities, such as natural language processing, to identify trends and make predictions.

Increase the pace of innovation

Extract value from your data with purpose-built health AI services and a well governed data lake to help you derive insights to deliver better care and quickly adapt to new challenges

Build on a trusted platform

AWS offers a mature, secure, and reliable cloud platform with a deep understanding of healthcare industry regulations (e.g. HIPAA, GDPR) and consistent data transparency and control to protect patient privacy. More healthcare customers trust AWS with their data than any other cloud provider.

Use cases

Machine learning is playing an increasingly important role in helping healthcare and life science organizations tackle new and complex challenges across key use cases.

Improve diagnostics
Manage population health
Accelerate drug discovery
Modernize care infrastructure

Improve diagnostics
Improve diagnostics

As the volume and accessibility of health data increases, machine learning is playing an important role in diagnosis. Machine learning helps to structure, normalize, and analyze health data, so healthcare and life science organizations can use it to make better and quicker decisions — be it precision diagnosis using genomic sequencing, early-state cancer detection, or advanced cardiac visualization with custom machine learning models. Purpose-built health AI services automatically transform health data in minutes, instead of weeks or months, so clinicians can accelerate diagnosis and provide early intervention.

Customer case studies

Machine Learning Services

Amazon SageMaker

Build predictive disease models with Amazon SageMaker.

Amazon Rekognition

Automate your medical image and video analysis with Amazon Rekognition.

Amazon HealthLake

Store, transform, query, and analyze health data with Amazon HealthLake.
Manage population health
Manage population health

Developing a better understanding of the health of a population can help policy makers and healthcare systems make data-driven decisions to care for millions of patients. Machine learning tools provide a chronological view of medical events to help healthcare organizations analyze population health trends and outcomes. Biopharma organizations can analyze large-scale population genomic studies. Customers can easily create a cohort of patients and their treatments, demographics, and tests and use advanced machine learning models to understand how a population changes over time to identify the most appropriate treatment for a patient population.

Customer case studies

Machine Learning Services

Amazon SageMaker

Build predictive disease models with Amazon SageMaker.

Amazon HealthLake

Store, transform, query, and analyze health data with Amazon HealthLake.
Accelerate drug discovery
Accelerate drug discovery

Pharmaceutical and biotech companies need to find innovative ways to more quickly and efficiently discover, develop, trial, manufacture, and commercialize therapeutics. Machine learning is leveraged across the pharmaceutical value chain from rapid experimentation for drug discovery to enabling smart manufacturing to post-market surveillance to detect adverse events.

Customer case studies

Machine Learning Services

Amazon SageMaker

Build predictive disease models with Amazon SageMaker.

Amazon Transcribe Medical

Automate the transcription of calls reporting adverse drug events with Amazon Transcribe Medical.

Amazon Translate

Translate reports into a common language with Amazon Translate.

Amazon Kendra

Introduce highly accurate, intelligent enterprise search service to accelerate drug development with Amazon Kendra.

Amazon Neptune

Build Knowledge Graphs for drug discovery, target identification and molecular design with Amazon Neptune.
Modernize care infrastructure
Modernize care infrastructure

The health industry is complex with a lot of manual, paper-based processes and health records. Using document classification, natural language understanding, and speech-to-text technologies, machine learning can simplify and automate processes to help improve efficiency, reduce hospital waste, and decrease physician burnout. Purpose-built health AI services and advanced machine learning models can help modernize the care infrastructure and reduce operational overhead, while at the same time support interoperability, like the Fast Healthcare Interoperable Resources (FHIR) industry standard.

Customer case studies

Machine Learning Services

Amazon HealthLake

Store, transform, query, and analyze health data with Amazon HealthLake.

Amazon Textract

Easily extract printed text, handwriting, and data from health documents with Amazon Textract.

Amazon Lex

Build conversational interfaces into any health application, like void assistants and digital front door applications, using voice and text with Amazon Lex.

Amazon Transcribe Medical

Accurately transcribe physician-patient conversations using automated speech recognition.

Amazon Comprehend Medical

Extract health data from free-form medical text like doctors’ notes, clinical trial reports, and patient health records.

Customer case studies

How can we accelerate time to insights?

Using Amazon SageMaker AstraZeneca analyzes commercial health data at scale, accelerating insights while reducing the manual workload of its data scientists. The ability to automate most of the machine learning development is essential as AstraZeneca faces an increasing amount of commercial data.

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How can we revolutionize the drug discovery process and bring drugs to market faster?

Using machine learning built on AWS, Moderna developed a new mRNA COVID-19 vaccine with unprecedented speed. Algorithms enable rapid experimentation cycles and help design mRNA and DNA sequences; they automate quality control data analyses, saving countless hours of manual review; and they automate logistics decisions.

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How can we give individuals access to critical healthcare information?

Using Amazon Comprehend Medical and Amazon Textract, Cambia Health Solutions can automatically extract information from medications, medical conditions, and procedures and document them in a single, user-friendly platform. This removes much of the human intervention from the work and enables better evaluation of patient health risks.

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How can we more efficiently extract important information from insurance claims forms?

Using Amazon Textract, Anthem is able to digitize and automate its claims process. Textract’s image-processing capability, ability to detect tables and forms and adherence to security and compliance standards – allows Anthem to quickly process thousands of claims each day.

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