Joshua Kunkes’ Post

In #healthcare, the conversation about generative #AI swings between high hopes and hard-hitting realism. On one side, the potential to transform patient experiences and operational efficiencies is undeniable. Yet, we're at a pivotal moment where excitement should not eclipse caution. The essence of integrating generative AI into healthcare isn't about technological triumphs alone but understanding its current limitations. It's a complex dance of innovation where patient safety and care quality cannot be compromised. This brings us to a critical point: the integration of such pioneering technology must be navigated with a keen awareness of its readiness and the overarching priority of patient welfare. This dialogue is more than a technology debate; it's about forging a responsible path forward. It's about collaboration among AI developers, healthcare practitioners, and regulatory bodies to ensure the technology genuinely meets healthcare's stringent standards. And it's about addressing broader concerns such as data privacy, security, and the ethical implications of AI use. The journey of bringing generative AI into healthcare is indeed filled with promise. However, our collective enthusiasm for innovation must be balanced with a careful consideration of its practical implications. As we venture into this new frontier, let's advocate for a responsible approach that keeps the well-being of patients at the heart of technological advancement. Read more on the debate 👉 https://lnkd.in/dGVDV-xi Need help with healthcare IT? 👉 https://lnkd.in/gSacdkv4 #technology #healthcareIT #generativeAI #SparkNav

As we witness the rapid advancement of generative AI, it's clear that its potential applications in healthcare are both exciting and complex. The recent article sheds light on the growing investments in generative AI efforts to revolutionize healthcare. However, as we delve deeper into this development, it's crucial to consider the implications and readiness of healthcare-focused generative AI for widespread implementation. The promise of generative AI in healthcare is undeniable, with the potential to enhance diagnostics, drug discovery, and personalized treatment plans. The article highlights the enthusiasm surrounding these advancements but also raises important questions about the ethical, regulatory, and practical considerations that must be addressed. Integrating generative AI in healthcare demands thoroughly examining its accuracy, safety, and potential biases. Moreover, the article prompts us to contemplate the readiness of healthcare systems, professionals, and regulatory frameworks to effectively harness the power of generative AI while safeguarding patient well-being. As professionals in the healthcare and AI sectors, we must reflect on the implications and challenges presented by the convergence of these fields. By fostering open dialogue and collaboration, we can navigate the complexities and ensure that generative AI in healthcare is harnessed responsibly and ethically. Read the full article here: https://lnkd.in/d2MJVfkP #AI #HealthcareInnovation #GenerativeAI #EthicalAI #HealthTech #ArtificialIntelligence

An interesting article on the use of generative AI in healthcare. Here is a summary: - Generative AI is increasingly being applied to healthcare by big tech companies like Google, Amazon and Microsoft as well as startups. However, not all experts are convinced it's ready for medical use cases. - A Deloitte survey found only around half of US consumers believe generative AI can improve healthcare access, wait times or costs. Experts cite limitations in its medical knowledge and lack of human expertise. - Studies show generative AI like ChatGPT makes errors in 83% of pediatric diagnoses and ranks the wrong diagnosis top in nearly 2/3 of cases reviewed by physicians. - There are also concerns generative AI could perpetuate biases and stereotypes in ways that negatively impact patient care and outcomes. - While imaging analysis is seen as a promising application, generative AI is not seen as ready to provide comprehensive medical advice or recommendations independently. - Significant challenges around privacy, security, liability, regulation and ensuring generative AI does not practice medicine must still be addressed. - Rigorous testing through randomized controlled trials is advocated to properly evaluate clinical benefits and risks before patient-facing deployment. - Guidelines call for transparent development and oversight to encourage diverse participation and allow for ongoing input and concerns to be raised. What do you think? Different studies are producing different findings and conclusions! Why not use generative AI to augment and assist healthcare professionals, not to replace them? #ai #genai #artificialintelligence #generativeai #healthcare #medicine #doctors #hospitals #chatgpt #physicians #medical

AI in Medicine: Boon or Bane? Generative AI is making strides in healthcare, backed by major tech and startups. However, concerns about its readiness, accuracy in complex medical tasks, and potential bias persist. Experts advocate rigorous validation, privacy safeguards, and human oversight before widespread adoption, emphasizing the technology's promise against its current limitations. #AIinMedicine #HealthcareTechnology #GenerativeAI #MedicalInnovation #EthicalConsiderations #Validation #PrivacyProtection #HumanOversight

As generative AI enters healthcare, reactions are mixed. While it promises enhanced access and efficiency, concerns about its readiness and accuracy prevail. What's your take on this innovation? https://buff.ly/4azaDly #HealthTech #AI #GenerativeAI

Innovative AI technology is freeing up providers' time by handling repetitive tasks and administrative duties, allowing them to focus on what matters most: their patients. But AI shouldn't replace human interaction. While these technologies offer valuable benefits, it's important to remember that the human connection at the heart of medicine is irreplaceable. AI should be seen as a tool to complement patient care, not replace it. https://lnkd.in/eArHa9vN #healthcare #technology #brandivoss #AI #artificialintelligence #futureofmedicine

This seems like a laudable goal. There is still much to be figured out with AI and how it can be used to enhance efficiency, streamline processes, and improve outcomes. As with many innovations, AI means different things to different people. A lot of work remains to determine the best and most responsible ways to implement it. This is another set of tools to help people work at the top of their license. #AI

Generative AI's rapid rise, led by OpenAI's ChatGPT, ignited global interest and hype, with numerous firms asserting transformative effects, particularly in healthcare. This overview delves into AI's varieties in healthcare, like machine learning and ambient AI, and their roles in medical imaging, drug discovery, and clinical documentation. It underscores the importance for health care leaders to judiciously select AI partners, emphasizing solutions specialized for healthcare workflows, ethical AI frameworks, deployment expertise, reliability, and extensive healthcare experience. #Sponsored #GenerativeAI #HealthcareInnovation #ChatGPTImpact #AIMedicalAdvances #EthicalAI #HealthTech #AIDeployment #AIinHealthcare #DigitalHealth #ClinicalAI

A must-read article. You might not agree with it, but it certainly makes the case we make which is understanding what AI can and can't do, and knowing how critical the underlying data and how that is organized and handled, is mission critical.

Why is building an algorithm and solution for clinical care so complex? Why does it require precision AI? And how is it different from a #generativeai tool? Our CEO Elad Walach shares his industry insights in this informative article. #healthcareai