Moving Too Fast Can Break People: Looking Back at HIMSS 2023
In the aftermath of the pandemic, our healthcare system rose to new challenges, delivered exceptional care, but also...
for the health of people
for the health of planet
for the health of business
FOR THE HEALTH OF PEOPLE: EQUITY
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“The work [with Synaptiq] is unprecedented in its scale and potential impact,” Mortenson Center’s Managing Director Laura MacDonald MacDonald said. “It ties together our center’s strengths in impact evaluation and sensor deployment to generate evidence that informs development tools, policy, and practice.”
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DATA STRATEGY
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A startup in digital health trained a risk model to open up a robust, precise, and scalable processing pipeline so providers could move faster, and patients could move with confidence after spinal surgery.
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PREDICTIVE ANALYTICS
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Thwart errors, relieve in-take form exhaustion, and build a more accurate data picture for patients in chronic pain? Those who prefer the natural albeit comprehensive path to health and wellness said: sign me up.
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MACHINE VISION
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Using a dynamic machine vision solution for detecting plaques in the carotid artery and providing care teams with rapid answers, saves lives with early disease detection and monitoring.
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INTELLIGENT AUTOMATION
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This global law firm needed to be fast, adaptive, and provide unrivaled client service under pressure, intelligent automation did just that plus it made time for what matters most: meaningful human interactions.
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Mushrooms, Goats, and Machine Learning: What do they all have in common? You may never know unless you get started exploring the fundamentals of Machine Learning with Dr. Tim Oates, Synaptiq's Chief Data Scientist. You can read and visualize his new book in Python, tinker with inputs, and practice machine learning techniques for free. |
Start Chapter 1 Now ⇢ |
Artificial intelligence (AI) and machine learning (ML) aren't synonymous. It’s a common mistake to use these terms interchangeably, but ML is a subset of AI, not a different word for the same idea. Learning the difference between ML and other types of AI is a step toward tech-literacy worth taking — especially if you’re a business leader, working professional, or student — because you almost certainly encounter them every day.
Artificial intelligence is a sub-discipline of computer science concerned with developing artificial systems capable of performing tasks that typically require human intelligence. We categorize AI into different subsets based on functionality. One of those subsets is machine learning, which involves teaching artificial systems to learn from data and improve their performance over time. ML-enabled systems can analyze vast amounts of data incredibly quickly and accurately. ML applications are everywhere; in fact, you probably used one to find this blog. Google, Twitter, and LinkedIn leverage ML algorithms to order search results and deliver recommendations.
You should familiarize yourself with these four common types of machine learning:
Synaptiq is an AI and data science consultancy based in Portland, Oregon. We collaborate with our clients to develop human-centered products and solutions. We uphold a strong commitment to ethics and innovation.
Contact us if you have a problem to solve, a process to refine, or a question to ask.
You can learn more about our story through our past projects, blog, or podcast.
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