Our Co-founder and CTO Jay Nanduri's latest article in his series on Truveta's AI approach focuses on how we ensure that the AI technologies used in Truveta Studio have the requisite accuracy and explainability, while also assuring fairness and avoidance of bias. Read the full article here: https://tr.vet/3XEu8p0 And catch up on his other posts in this series: 🪨 Generating data gravity: https://tr.vet/4cJUJWd 🛣️ Truveta's journey applying generative AI to advance healthcare: https://tr.vet/3RMtEJK #HealthData #HealthAI #HealthInnovation #AI #GenerativeAI #LargeLanguageModel #LLM #AIBias #BiasAvoidance #HealthcareAI #HealthcareInnovation #HealthTech #HealthcareTech #MedicalTechnology #MedTech #MedicalAI #MedicalInnovation #MedicalData #HealthcareData #DigitalTransformance
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Unlocking the potential of generative AI in healthcare - a topic that is near and dear to our hearts. A recent article published by Healthcare IT News highlights three crucial steps that healthcare organizations need to embrace in order to harness the power of Generative AI responsibly. From enhancing patient care to improving diagnostic accuracy, it is no secret that this technology holds immense promise. This is a pivotal time for AI, and it is radically changing how healthcare is delivered. Be sure to check out these 3 steps, and share your thoughts in the comments - we’d love to hear your feedback. #HealthcareAI #InnovationInHealthcare #AIEthics #FutureofHealthcare #GenerativeAI” https://lnkd.in/g3wVRsq5
Three steps healthcare organizations can take to use generative AI responsibly
healthcareitnews.com
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Unlocking the Power of Generative AI in Healthcare: 3 Key Steps Responsible adoption of cutting-edge AI technologies is key to better patient care and outcomes. Here are three key steps to responsibly use generative AI in healthcare: 1. Understand the Ethics: Develop a profound understanding of the ethical implications surrounding Generative AI to navigate the fine line between innovation and responsibility. 2. Data Governance: Ensure robust data governance. Clean, accurate, and unbiased data is the lifeblood of AI systems. Establish strict protocols for data collection, storage, and usage to build trust. 3. Human Oversight: Never underestimate the importance of human oversight. While AI can work wonders, human experts are essential for decision-making and validation. Check out the full article for an in-depth look at these three key steps: https://lnkd.in/g3wVRsq5
Three steps healthcare organizations can take to use generative AI responsibly
healthcareitnews.com
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Our Co-founder & CTO Jay Nanduri has been busy reflecting on Truveta's AI journey. Here, he outlines six challenges we're facing - including scaling our AI models for growth, ensuring privacy and compliance, and delivering accuracy - and the solutions we're building to tackle them: https://tr.vet/44cKd6y #AI #LargeLanguageModel #LLM #MachineLearning #ArtificialIntelligence #Innovation #HealthcareAI #HealthAI #HealthInnovation #HealthcareInnovation #HealthTech #HealthData #MedTech #HealthcareTech #HealthcareData #BigData #GenerativeAI #AIModel
Our journey of applying generative AI to advance healthcare
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As early adopters and industry leaders scale their Generative AI deployments beyond PoCs into enterprise value chains, there needs to be a measurable way to check the quality and trust of the solution. This is more so in healthcare. The industry needs a built for healthcare trust framework. Sridhar Turaga shares his insights on CitiusTech's built for Healthcare, "Quality and Trust" framework for measuring our client's model across 7 dimensions of accuracy, calibration, robustness, fairness, bias, toxicity, and efficiency. Advancing the acceleration of Gen AI adoption with Trust.
“There have been no established technology-agnostic and platform-agnostic solutions that measure the quality and trust of healthcare generative AI, end-to-end," says Sridhar Turaga, Sr. Vice President, Data and Analytics Practices at CitiusTech, as he shares insights on Generative AI. Read the article to learn more about how CitiusTech’s solutions enable clients to measure their models for accuracy, calibration, robustness, fairness, bias, toxicity, and efficiency. Click on the image to read more. #CitiusTech #HealthcareLimitless #GenerativeAI #AI #HealthcareTechnology
Generative AI in Your Desk Drawer: How to Get There
https://www.healthcareittoday.com
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EVP at CitiusTech | Strategy & Operations Leader | Head of Department/s | Digital Transformation Evangelist | Diversity Champion | CSR Captain | Toastmasters Enthusiast
Tailoring Generative AI models to specific industries is essential. In healthcare, protecting personal data is a distinct challenge. Ergo, healthcare organizations must critically assess the appropriateness of relying on general-purpose solutions provided by major tech companies. In a recent Healthcare IT Today interview, my colleague Sridhar Turaga discusses CitiusTech's dedicated Generative AI Quality & Trust solution, specifically designed to evaluate Gen AI quality and readiness in healthcare settings... #genai; #generativeai; #genaitrends; #genairevolution; CitiusTech; FluidEdge Consulting - a CitiusTech company; SDLC Partners, L.P. - A CitiusTech Company; Wilco Source
“There have been no established technology-agnostic and platform-agnostic solutions that measure the quality and trust of healthcare generative AI, end-to-end," says Sridhar Turaga, Sr. Vice President, Data and Analytics Practices at CitiusTech, as he shares insights on Generative AI. Read the article to learn more about how CitiusTech’s solutions enable clients to measure their models for accuracy, calibration, robustness, fairness, bias, toxicity, and efficiency. Click on the image to read more. #CitiusTech #HealthcareLimitless #GenerativeAI #AI #HealthcareTechnology
Generative AI in Your Desk Drawer: How to Get There
https://www.healthcareittoday.com
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One of the great challenges we have seen businesses face in recent years is how they approach data and #analytics (and now #AI) when their industries are undergoing major transformation. It’s hard enough to create a #datadriven culture, compete on analytics, develop data-driven products and services, and so forth under normal business conditions. Learn how to embrace AI: https://lnkd.in/eRvxSWJ
Embracing AI When Your Industry Is in Flux | Thomas H. Davenport and Randy Bean
sloanreview.mit.edu
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One of the great challenges we have seen businesses face in recent years is how they approach data and #analytics (and now #AI) when their industries are undergoing major transformation. It’s hard enough to create a data-driven culture, compete on analytics, develop data-driven products and services, and so forth under normal business conditions. But doing it while your business and industry are transforming the old line of changing out a jet engine while the plane is flying through turbulence at 35,000 feet — is really tough. Read about embracing AI when your industry is in flux: https://lnkd.in/eRvxSWJ #datadriven
Embracing AI When Your Industry Is in Flux | Thomas H. Davenport and Randy Bean
sloanreview.mit.edu
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Group Head Data & Analytics @ Ahli United Bank | Business Executive, Data & Analytics Strategies, Practical Data Transformation and hands-on Implementation
A good article from Randy Bean and Tom Davenport regarding the challenges of organizations to get their data and analytics foundations in place while they are facing the next challenges, how too leverage on AI? The first category they describe for AI use cases, hopefully brings us all back to reality; "The first category of AI work is the simplest and most straightforward. Automation — robotic process and more intelligent automation — is being used to reduce the manual labor burden in administrative processes." #datamonetization #ai #machinelearning #Artificialintelligence #genai #data #analytics #cdao
One of the great challenges we have seen businesses face in recent years is how they approach data and #analytics (and now #AI) when their industries are undergoing major transformation. It’s hard enough to create a data-driven culture, compete on analytics, develop data-driven products and services, and so forth under normal business conditions. But doing it while your business and industry are transforming the old line of changing out a jet engine while the plane is flying through turbulence at 35,000 feet — is really tough. Read about embracing AI when your industry is in flux: https://lnkd.in/eRvxSWJ #datadriven
Embracing AI When Your Industry Is in Flux | Thomas H. Davenport and Randy Bean
sloanreview.mit.edu
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“There have been no established technology-agnostic and platform-agnostic solutions that measure the quality and trust of healthcare generative AI, end-to-end," says Sridhar Turaga, Sr. Vice President, Data and Analytics Practices at CitiusTech, as he shares insights on Generative AI. Read the article to learn more about how CitiusTech’s solutions enable clients to measure their models for accuracy, calibration, robustness, fairness, bias, toxicity, and efficiency. Click on the image to read more. #CitiusTech #HealthcareLimitless #GenerativeAI #AI #HealthcareTechnology
Generative AI in Your Desk Drawer: How to Get There
https://www.healthcareittoday.com
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AI Entrepreneur. Keynote Speaker, Interests in: AI/Cybernetics, Physics, Consciousness Studies/Neuroscience, Philosophy: Ethics/Ontology/Maths/Science. Life and Love.
Title: AI in Healthcare: The Jobs to be Done See… https://lnkd.in/dCcbJ8Ct In enterprise healthcare, there are many “Jobs to be Done” (JTBD) for AI. To this end, we present the first part of the 6th episode of the Digital Health Go-to-Market Playbook series–Commercializing AI in Healthcare. This piece, Part A, uses Clay Christensen’s Jobs to be Done lens, along with an assessment of viable product wedges and business models, to share what we see as the most promising applications of AI in enterprise healthcare. We also describe which use cases are more conducive to the application of generative AI in the form of large language models (LLMs) versus traditional machine learning (ML). AI Jobs to be Done in enterprise healthcare Enterprise healthcare tasks are well-suited to AI for two reasons: 1/ The tasks are based on large amounts of complex and esoteric data that must be synthesized, in real time, to inform a consequential decision or action. 2/ The tasks are labor-intensive, with low historical adoption of traditional software products to facilitate them. We’ve previously described the leapfrog opportunity that exists because of this point
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Chief Executive Officer at USA and International Research Inc.
2wEnsuring AI accuracy, explainability, fairness, and bias avoidance is crucial for impactful healthcare innovations. Looking forward to reading Jay Nanduri's insights on Truveta's approach! #AI #HealthcareInnovation