The hottest Healthcare Technology Substack posts right now

And their main takeaways
Category
Top Health & Wellness Topics

When Doctors With A.I. Are Outperformed by A.I. Alone

Ground Truths • 10935 implied HN points • 02 Feb 25
🏥 Health & Wellness Artificial Intelligence Diagnostics Patient Care Healthcare Technology
  1. A.I. is often outperforming doctors in diagnosing medical conditions, even when doctors use A.I. as a tool. This means A.I. can sometimes make better decisions without human involvement.
  2. Doctors might not always trust A.I. and often stick to their own judgment even if A.I. gives correct information, leading to less accurate diagnoses.
  3. Instead of having doctors and A.I. work on every case together, we should find specific tasks for each. A.I. can handle simple cases, allowing doctors to focus on more complex problems where their experience is vital.

Illumina@JPM - More Clinical!

ASeq Newsletter • 29 implied HN points • 15 Jan 25
🕹 Technology Biotechnology Healthcare Technology Genomics Innovation
  1. Illumina's revenue has been flat but they are focusing on clinical applications, now making up 56% of their market. This indicates a shift in strategy towards health-related services.
  2. The company continues to reduce its cost per gigabyte of sequencing, although it remains higher than some competitors. They're positioning themselves to provide more value and insights rather than just cheaper sequencing.
  3. Despite the competitive pressure on pricing, Illumina aims to deliver high-quality insights at a lower overall cost instead of racing to the bottom with pricing like some other vendors.

Comparing Human, LLM & LLM-RAG Responses

Cobus Greyling on LLMs, NLU, NLP, chatbots & voicebots • 59 implied HN points • 09 Feb 24
🕹 Technology Artificial Intelligence Machine Learning Healthcare Technology Research Studies Data science
  1. The study compared answers from humans, a basic LLM, and an LLM that uses RAG to see which is most accurate in healthcare. The LLM with RAG performed the best.
  2. Using RAG, the model was much quicker than humans, taking only about 15-20 seconds. Humans took around 10 minutes to respond.
  3. GPT-4, especially with RAG, showed high accuracy and can support doctors by providing fast and reliable answers, but humans should still check the information.
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GMO bacteria to detect colorectal cancer?

Tessa Fights Robots • 23 implied HN points • 23 Feb 24
🏥 Health & Wellness Cancer Healthcare Technology
  1. Scientists are experimenting with genetically modified bacteria to detect cancerous DNA, particularly in colorectal cancer, by programming them to signal the uptake of cancerous DNA.
  2. The engineered bacteria, named CATCH, shows promise in detecting diseases like infections and cancers using cell-free DNA as input, but more refinement and safety evaluations are needed before clinical use.
  3. The goal is not just disease detection, but also pairing the detection with appropriate biological therapy, allowing for real-time response to diseases detected.

The Oracle Effect

Sector 6 | The Newsletter of AIM • 19 implied HN points • 02 Oct 23
🕹 Technology Cloud Computing Artificial Intelligence Enterprise Software Data Management Healthcare Technology
  1. Oracle wants to make the cloud more accessible and open for everyone. They believe it's important for all companies to have equal access to cloud technology.
  2. They are pushing to enhance the use of generative AI in business applications and are working on new tools for industries like healthcare.
  3. Oracle has set an ambitious target to grow their company by $15 billion in three years. They want to stand out among big cloud providers like AWS and Google Cloud.

Data Science Weekly - Issue 435

Data Science Weekly Newsletter • 19 implied HN points • 24 Mar 22
🕹 Technology Data science Machine Learning Artificial Intelligence Healthcare Technology Statistical Analysis
  1. Algorithmic assessments can help ensure that healthcare technology benefits everyone involved. It's important to evaluate how data is used in these systems.
  2. Relying solely on deep learning for electronic medical records may not be the best idea right now. Instead, better IT support is needed to improve healthcare systems.
  3. Many claims about explaining AI technology are misleading. Experts agree that what we currently call 'explainable AI' often falls short of being truly understandable.

Why AI doctors should not be FDA regulated

More is Different • 7 implied HN points • 15 Jul 23
🕹 Technology AI Regulation Medical AI Healthcare Technology
  1. The current FDA system for AI regulation may not be sustainable due to the growing number of applications and the high costs involved in getting AI systems approved.
  2. The FDA is not equipped to regulate general-purpose AI systems like advanced AI doctors, leading to potential delays in innovation and challenges in handling new technologies.
  3. People have the right to access information from AI systems for medical advice, similar to consulting books or other resources, which raises questions about the need for FDA regulation.

Book review: "Innovation Breakdown"

More is Different • 3 implied HN points • 29 Jun 23
🏥 Health & Wellness FDA Regulations Patient Safety Regulatory Challenges Healthcare Technology
  1. Innovation Breakdown tells the story of a startup harmed by FDA actions, highlighting the challenges of bringing a new medical device through the FDA.
  2. Medical device approvals at the FDA involve complex processes with regulatory uncertainties and the potential for regulatory roadblocks.
  3. The book raises questions about regulatory transparency, advocating for policy reforms to speed up approvals, reduce uncertainty, and balance strictness and effectiveness testing.

Axial Discovery - Voice in healthcare

Discovery by Axial • 3 implied HN points • 20 Feb 23
🏥 Health & Wellness Healthcare Technology Patient Care Virtual assistants
  1. Voice technology in healthcare can help patients and doctors by transcribing conversations and reducing errors.
  2. Companies like Abridge and Suki are developing voice products to enhance patient care and doctor efficiency.
  3. Building voice assistants for healthcare has potential for personalized patient and doctor interactions, but faces technical challenges and privacy concerns.

Data Science Weekly - Issue 241

Data Science Weekly Newsletter • 19 implied HN points • 05 Jul 18
🕹 Technology Artificial Intelligence Data science Machine Learning Software Development Healthcare Technology
  1. AI can create fun and interesting game titles, showing its creativity in areas like gaming.
  2. Some algorithms are getting good at detecting medical issues, like heart attacks, nearly as well as doctors can.
  3. New tools are making it easier for people to build AI systems without needing to know how to code.

[in case you missed it] Data Science Weekly - Issue 435

Data Science Weekly Newsletter • 0 implied HN points • 27 Mar 22
🕹 Technology Data science Machine Learning Artificial Intelligence Healthcare Technology Software Development
  1. Algorithmic impact assessments are important for using data in healthcare. They help ensure that the technology is safe and beneficial for everyone involved.
  2. Using deep learning on electronic medical records may not work well right now. It might be better to focus on improving IT support and fixing underlying structures instead.
  3. There's a problem with how we explain AI systems. Many explanations offered today don't truly help us understand how these systems work.

General Catalyst Buys a Hospital

Discharge Summary • 0 implied HN points • 21 Jan 24
🏥 Health & Wellness Healthcare Technology Healthcare Innovation Patient Care Medical AI
  1. General Catalyst acquires Summa Health, a nonprofit health system, shifting from non-profit to for-profit.
  2. Concerns arise about revenue models and potential changes in practice infrastructure with the acquisition.
  3. The acquisition aims to modernize healthcare with the latest technology, potentially impacting patient care and provider preference.