AWS for Industries

Tag: amazon sagemaker

drone flying in front of the turbines

Automating Wind Farm Maintenance Using Drones and AI

Introduction Turbine maintenance is an expensive, high-risk task. According to a recent analysis from the news website, wind farm owners are expected to spend more than $40 billion on operations and maintenance over a decade. Another recent study finds by using drone-based inspection instead of traditional rope-based inspection, you can reduce the operational costs by 70% […]

Architecture deployed with AWS SAM shown by orange dashed box

AI-Driven Visual Inspection of Wind Turbines Based on Drone Imaging

Introduction Keeping wind turbines operational also means keeping them well maintained. One of the steps in maintenance is regular visual inspection. Wind farm operation and maintenance companies started to utilize drones with attached cameras to perform visual inspections. According to a recent study, drone-based inspection reduces costs by up to 70% and decreases revenue lost […]

Training Machine Learning Models on Multimodal Health Data with Amazon SageMaker

Training Machine Learning Models on Multimodal Health Data with Amazon SageMaker

This post was co-authored by Olivia Choudhury, PhD, Partner Solutions Architect; Michael Hsieh, Sr. AI/ML Specialist Solutions Architect; and Andy Schuetz, PhD, Sr. Startup Solutions Architect at AWS. This is the second blog post in a two-part series on Multimodal Machine Learning (Multimodal ML). In part one, we deployed pipelines for processing RNA sequence data, clinical […]

Example visualization of a CT scan, with lung tumor mask overlaid in yellow

Building Scalable Machine Learning Pipelines for Multimodal Health Data on AWS

This post was co-authored by Olivia Choudhury, PhD, Partner Solutions Architect; Michael Hsieh, Senior AI/ML Specialist Solutions Architect; and Andy Schuetz, PhD, Sr. Partner Solutions Architect. Healthcare and life sciences organizations use machine learning (ML) to enable precision medicine, anticipate patient preferences, detect disease, improve care quality, and understand inequities. Rapid growth in health information […]

Variant call files overview

Machine Learning Leukemia diagnosis at Munich Leukemia Lab with Amazon SageMaker

Munich Leukemia Lab (MLL) is a leading global institution for leukemia diagnostics and research, operating within a highly innovative environment. MLL aims to shape the future of hematological diagnostics and therapy through state-of-the-art molecular and computational methodologies. To this end, MLL partnered with the Amazon Machine Learning Solutions Lab (MLSL) and Mission Solutions Team (MST) […]

Algorithmic Trading on AWS with Amazon SageMaker and AWS Data Exchange

It is well known that the majority of stock transactions are automated (as described here and here), for example using applications or “robots” implementing a trading strategy. More recently, an emerging trend in the financial services industry is the movement of trading solutions, such as algorithmic trading solutions, to the cloud (as described here and […]

[In the News] The Intelligent Era: Design, Detect, Discover

This article originally appeared on BBC StoryWorks. How machine learning is changing the pharmaceutical industry and reshaping the way drugs are produced in the 21st century The scale of the pharmaceutical industry is staggering. There are millions of patients to take care of, billions of data points generated by every clinical trial—and that’s before you […]

Building a multi-channel, data driven patient engagement platform with AWS

In today’s digitally transformed world, it’s more important than ever to have a deeper understanding of your patient’s attitude and behavior, and to engage them with personalized content through the channels that they prefer in order to provide efficient and personalized patient care. In addition, with today’s value-based healthcare, the patient is the center of […]