Industry-aware analytics using Azure Synapse database templates
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Frank
- September 4, 2022
- Agriculture
- annuities
- automotive
- azure friday
- Azure Synapse
- Azure Synapse Analytics
- Banking
- business context
- casualty
- clinical trials
- consumer goods
- converged analytics
- Data Lake
- energy & commodity trading
- enterprise templates
- freight
- fund management
- Genomics
- Healthcare
- healthcare providers
- industry standard
- insurance
- Lakshmi Murthy
- life insurance
- Logistics
- Manufacturing
- oli & gas
- pharmaceuticals
- property
- Retail
- Scott Hanselman
- Silos
- simplify
- template
- utilities
Lakshmi Murthy joins Scott Hanselman to show how to build an enterprise data model using Azure Synapse database templates to add rich business context to data and drive meaningful analytics.
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Quantum Computing Applied to Healthcare
This 30 minutes session talks about Quantum computing and how we can take advantage to solve serious health problems, diagnose patients, and venture into the creation of medicines, and disease prevention among other use cases.
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Lessons Learned from Deidentifying 700 Million Patient Notes
Providence embarked on an ambitious journey to de-identify all our clinical electronic medical record (EMR) data to support medical research and the development of novel treatments. This talk shares how this was done for patient notes and how you can achieve the same. First, we built a deidentification pipeline using pre-trained deep learning models, fine-tuned […]
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Delivering better patient outcomes with the Lakehouse for Healthcare and Life Sciences | Databricks
The healthcare and life sciences industry is complex, but the mission is clear: improve patient outcomes. Delivering on this mission begins with data. The potential is there, but the data for so many organizations remains out of reach. Powered by the Databricks Lakehouse Platform, organizations across the industry are tapping into data and AI to […]
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Building a Health DAO with GitHub CoPilot
It’s been a while since I featured a Siraj Raval video. I still like his teaching style and Decentralized Autonomous Organizations (DAOs) are an important emerging topic. In this episode, we’ll build a simple DAO that let’s users submit their health data to a marketplace and let’s health organizations buy that data, with the proceeds […]
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Building Deep Learning Models for Digital Pathology Image Analysis
Keen Eye is an AI Platform company building deep learning models to guide better drug development and diagnostics. They support the pathologists to deliver accurate, standardized and undiscovered tissue insights in research and clinical studies. Keen Eye has migrated from an on-premise infrastructure to full AWS Cloud service leveraging EKS, S3, SageMaker and more.
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NVIDIA CEO Jensen Huan on the Industrial HPC Revolution
Industrial high performance computing (HPC) is at its tipping point. The combination of simulation, accelerated computing, and #AI are bringing the performance and scale required to tackle real-world, industrial problems. This presentation blew my mind.
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GTC 2021 Keynote with NVIDIA CEO Jensen Huang
NVIDIA CEO Jensen Huang delivers the #GTC21 keynote, where he introduced a number of amazing breakthroughs.
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An MIT Engineer Built His Own Bionic Leg
At MIT’s Media Lab, researchers are developing prosthetic limbs that users can control with their minds, making a robotic foot move as seamlessly as a biological one.
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Reliable Machine Learning Systems
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Frank
- January 14, 2020
- AI research
- Algorithms
- bacteria
- Biology
- classification
- Computer Science
- Deep Learning
- diagnosis
- Genetics
- Genomics
- google research
- Healthcare
- healthcare AI
- LSTM network
- Machine Learning
- Math
- Mathematics
- Medicine
- Neural Network
- neurIPS
- Python
- recurrent network
- Siraj Raval
- Statistics
- TensorFlow
Siraj Raval has a video exploring a paper about genomics and creating reliable machine learning systems. Deep learning classifiers make the ladies (and gentlemen) swoon, but they often classify novel data that’s not in the training set incorrectly with high confidence. This has serious real world consequences! In Medicine, this could mean misdiagnosing a patient. […]
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