Latest posts tagged with #mlsky on Bluesky
Figure 1. Health Care Needs and Resources by Rural–Urban Classification Using the 2013 National Center for Health Statistics Urban–Rural Classification Scheme for Counties.
A new Perspective examines the misalignment between health needs, health care resources, and #AI implementation capacity, demonstrating that Hart’s inverse care law persists in the AI era. Read the full Perspective: nejm.ai/4v0RvHx
#MedSky #MLSky
Figure 1. The AI Governance Iceberg Demonstrating Visible and Hidden AI Use in Health Care.
Health systems’ lack of engagement with consumer #AI tools worsens their risk by eliminating institutional visibility and protections. Ötleş et al. describe the scope of this problem and why health systems need to reform their approach to AI governance. nejm.ai/4sQFxz6
#MedSky #MLSky
Figure 3. Clinical Impact Study.
Original Article by H.-Y. Zhou et al.: MedVersa: A Generalist Foundation Model for Diverse Medical Imaging Tasks nejm.ai/4bVAiYz
#AI #MedSky #MLSky
Is Half of All Advertising Spend Wasted?
In this week's issue of Causal Python Weekly:
- David Rohde on why even granular digital data often can't tell you which half of your ad budget is working
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#CausalSky #EconSky #EpiSky #StatSky #MLSky
No one opts out of health care. That’s the moral and operational reality. On NEJM AI Grand Rounds, Dr. Kyunghyun Cho argues #AI should help systems care better under constraints. If a tool can’t reduce friction at the bedside, what is it really for? Full episode: nejm.ai/ep40
#MedSky #MLSky
Figure 1. Strengthening the Reporting of Observational Studies in Epidemiology Inclusion Flowchart.
Figure 2. Transitions in Care Intentions from Preassessment to Postassessment Time Points.
Figure 3. Transitions between Preassessment Intentions and Actual Behavior.
Original Article by F. Cotte et al.: From Advice to Action — Real-World Behavior of Patients Using an Integrated Diagnostic Decision Support System for Navigating the Health Care System nejm.ai/4rENohz
#AI #MedSky #MLSky
Sometimes expertise becomes a trap. On NEJM AI Grand Rounds, Dr. Kyunghyun Cho reflects on how we can reconsider our perspective to unlock progress. Hear more from Dr. Cho in the full episode: nejm.ai/ep40
#AI #MedSky #MLSky
We Often Think About Randomized Trials as "the Gold Standard" for Causal Inference.
And yet we almost as often forget to ask what information they provide and under what circumstances.
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#CausalSky #EconSky #EpiSky #StatSky #MLSky #ABTesting
1/7 🧠 HUMAN NEURONS LEARN TO PLAY DOOM ON A CHIP 🧠
Scientists witness 200,000 living brain cells navigating the 1993 shooter.
This breakthrough blends biology and silicon, redefining computing.
Source: Deni Béchard,
Scientific American
#AISky #MLSky #MedSky #BioComputing #Doom
Figure 1. Study Overview.
The authors of a new article show that MedVersa, a model trained on millions of medical images, matches or outperforms task-specific systems while producing clinically equivalent radiology reports and reducing reporting time and discrepancies. Learn more: nejm.ai/4bVAiYz
#AI #MedSky #MLSky
What If We Reversed Bayes to Test How Robust Our Findings Are to Skepticism?
In this week's issue of Causal Python Weekly:
- Lu Qian's new blog post on Reverse Bayes and evidence
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#CausalSky #EconSky #EpiSky #MLSky #StatSky
When a research path becomes “predictable,” is it still research or product development? On NEJM AI Grand Rounds, Dr. Kyunghyun Cho draws a hard line between discovery and scaling. In health care, where should each live, and who should own the risk? Learn more: nejm.ai/ep40
#AI #MedSky #MLSky
Is the effect heterogeneity in your data real?
Testing effect homogeneity and confounding with mixed data
In their new working paper, Ana Paula Armendariz and Martin Huber propose a framework for testing the...
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#CausalSky #EconSky #EpiSky #StatSky #MLSky
If you not already have done so, I strongly recommend to read this beautiful, in-depth and hands-on article about how quantization works.
It may be the missing piece for how to understand how modern LLMs work. #MLSky 🧪
A paper in The Laryngoscope presents the first successful use of a cervical plexus block for persistent globus pharyngeus, offering a new clinical pathway for chronic throat sensations.
bit.ly/4lOpOOh
#ArtificialIntelligence #BiomedicalInformatics #MedSky #MedAI #AISky #AcademicSky #MLSky
Figure 1. Strengthening the Reporting of Observational Studies in Epidemiology Inclusion Flowchart.
An AI-powered digital front door tool used in Portugal was associated with reduced patient uncertainty, meaningful shifts in care-seeking behavior, and a substantial improvement in the appropriateness of health care utilization. Full study results: nejm.ai/4rENohz
#AI #MedSky #MLSky
Turns out generative AI can sometimes make some very convincing radiographs, and radiologists (and LLMs) struggle to catch all the fakes.
#MLsky #medsky
www.evidencetriage.com/p/deepfake-d...
New Review 💬 Beyond convolutions and supervised learning with transformers and representation learning for retinal image analysis: www.sciencedirect.com/science/arti...
#ArtificialIntelligence #BiomedicalInformatics #MedSky #MedAI #AISky #AcademicSky #MLSky #OpenScience
👀 @sebastianraschka.com wrote an epic blog post accompanying his LLM architecture gallery (see below):
"A Visual Guide to Attention Variants in Modern LLMs"
Highly recommended to check both out -> magazine.sebastianraschka.com/p/visual-att...
#MLsky
My PI Benjamin Smarr breaks down how Darth Vader’s suit streams biometrics through a brain–computer interface.
Now I’m just trying to use wearable data to enhance my Force sensitivity.
skywalkingthroughneverland.com/star-warsolo...
#AcademicSky #MLSky #SciFiTech
A career in #AI doesn’t always start with a plan. Sometimes it starts with a recession, a random lab assignment, and a decision to keep going. On NEJM AI Grand Rounds, Dr. Kyunghyun Cho reminds us that serendipity favors the curious. Listen to the full episode: nejm.ai/ep40
#MedSky #MLSky
Dropbox Reallocated $25M of Their Marketing Budget After a Causal Study.
In this week's issue of Causal Python Weekly:
- Alberto D. Horner reviews a new End-to-End Estimation for Counterfactual Fairness by Yuchen Ma et al.
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#CausalSky #EconSky #EpiSky #StatSky #MLSky
ApplyPolygenicScore functionality. Application of ApplyPolygenicScore functions demonstrated in a case study of 1071 individuals from the TCGA database, diagnosed with bladder (BLCA), liver (LIHC), or uterine (UCEC) cancer. A. Recommended workflow when implementing functions provided by ApplyPolygenicScore . A set of preprocessing functions convert polygenic risk score model (PGM) weight files into BED-formatted genomic coordinate files for suggested use in filtering VCF genotype data to desired coordinates. PGM application functions facilitate genetic data importation and weighted sum computation. Visualization functions provide summary information on computed PGSs and phenotype data. Solid arrows indicate required inputs and dotted arrows indicate optional inputs. B. BMI PGS densities, cohort-wide and by categorical phenotypes, computed in the case study cohort and automatically plotted by the create.pgs.density.plot function. C. Correlations of PGSs from (B) with continuous phenotypes automatically plotted by the create.pgs.with.continuous.phenotype.plot function. D. Receiver-operator curves plotted by the analyze.pgs.binary.predictiveness function depicting the performance of the PGSs from (B) to predict obesity status as a sole predictor (top) and with covariates age at diagnosis, sex, and the first 10 principal components of genetic ancestry (bottom). Positive obesity status is defined as BMI ≥ 30. E. From top to bottom: percentile rank of PGSs from (B) for each individual in ascending order, decile and quartile covariate bars, categorical phenotype covariate bars, and continuous phenotype heatmaps. Nicole Zeltser; Rachel M.A. Dang; Rupert Hugh-White; Daniel Knight; Jaron Arbet; Paul C. Boutros
🚀 ApplyPolygenicScore encourages the research community to extend the findings of the statistical genetics niche, facilitating broader use of PGSs and subsequent novel discovery: bit.ly/41jRDnS
#ArtificialIntelligence #BiomedicalInformatics #MLSky #AISky #MedSky #AcademicSky #SciSky #OpenScience
Page 1 of "Response to Spillover Effects in Randomized Evaluations of Translational AI” Read the full letter at ai.nejm.org.
Richard K. Leuchter, MD, William B. Turner, BA, and David Ouyang, MD, respond to a letter about their Perspective “Evaluating Translational AI: A Two-Way Moving Target Problem.” Read the full response: nejm.ai/4cQzu8d
#AI #MedSky #MLSky
Folks believe LLMs will just keep getting better forever, as if transformer-based models have no limits.
Wait until they’re profitable… they’re gonna suck.
Facebook, Google, YouTube, celebrated when they were losing money. Now the robber barons of a new gilded age.
#AcademicSky #MLSky #AIEthics
Ignore AI in #radiology at your peril, unfortunately.
Interestingly, however, as this (very small) report notes – *where* AI fits in the workflow might matter as far as a perceived "duty of care" to the a patient harmed by a missed diagnosis.
#medsky #mlsky
www.evidencetriage.com/p/more-littl...
New Review in @springernature.com 💬 Lithium offers a unique paradigm for understanding and potentially treating age-related decline in multiple organ systems at subclinical dosage and concentration.
bit.ly/4siRZqL
#ArtificialIntelligence #BiomedicalInformatics #AISky #MLSky #MedSky #MedAI
