1. 21 Sep 2026

    Artificial Intelligence and Anatomical Variation: A Narrative Review of Detection ...

    ... multimodal AI applications. This review therefore aims to characterize direct and variation-relevant AI applications, distinguish variant-specific ...

    www.cureus.com ↗
  2. 21 Sep 2026

    Artificial Intelligence and Anatomical Variation: A Narrative Review of Detection ...

    ("artificial intelligence" OR "machine learning" OR "deep learning" OR "convolutional neural network" OR "large language model" OR "vision ...

    www.cureus.com ↗
  3. 21 Sep 2026

    Artificial Intelligence and Anatomical Variation: A Narrative Review of Detection ...

    ("artificial intelligence" OR "machine learning" OR "deep learning" OR "convolutional neural network" OR "large language model" OR "vision ...

    www.cureus.com ↗
  4. 21 Sep 2026

    Artificial Intelligence and Anatomical Variation: A Narrative Review of Detection ...

    Education and foundation models, ("large language model" OR "vision-language model" OR ChatGPT OR "artificial intelligence") AND ("anatomy ...

    www.cureus.com ↗
  5. 17 Sep 2026

    Computational screening of oncogenic genetic variations in tumor suppressor proteins ...

    We employed a deep learning-based graph neural network model to identify genes exhibiting both dysregulated expression and high mutation propensity in ...

    journals.plos.org ↗
  6. 15 Sep 2026

    Ground Truth Is a Myth, Researcher Says - Communications of the ACM

    ... AI researcher Barbara Plank says this variation is valuable ... AI, alignment problems, and agentic AI. In all these domains, there may ...

    cacm.acm.org ↗
  7. 15 Sep 2026

    Ground Truth Is a Myth, Researcher Says - Communications of the ACM

    While much of machine learning is built around the assumption of a single ground truth that treats variation as noise, AI researcher Barbara Plank ...

    cacm.acm.org ↗
Sources

Where this comes from

Artificial Intelligence — Google

https://www.google.co.in/alerts/feeds/05832220720342067762/1990879549…

401 items Polled 22 Sep, 18:24 UTC 200

Agentic AI — Google

https://www.google.co.in/alerts/feeds/05832220720342067762/4849751788…

401 items Polled 22 Sep, 18:24 UTC 200

AI Agents — Google

https://www.google.co.in/alerts/feeds/05832220720342067762/4849751788…

401 items Polled 22 Sep, 18:24 UTC 200

Data Science — Google

https://www.google.co.in/alerts/feeds/05832220720342067762/4836803184…

401 items Polled 22 Sep, 18:24 UTC 200

Large Language Model — Google

https://www.google.co.in/alerts/feeds/05832220720342067762/8510459957…

401 items Polled 22 Sep, 18:24 UTC 200

Machine Learning — Google

https://www.google.co.in/alerts/feeds/05832220720342067762/4836803184…

401 items Polled 22 Sep, 18:24 UTC 200

Deep Learning — Google

https://www.google.co.in/alerts/feeds/05832220720342067762/1643871049…

401 items Polled 22 Sep, 18:24 UTC 200

LLMs Alignment — Google

https://www.google.co.in/alerts/feeds/05832220720342067762/5121641697…

45 items Polled 22 Sep, 18:24 UTC 200

AI Alignment — Google

https://www.google.co.in/alerts/feeds/05832220720342067762/1764885284…

401 items Polled 22 Sep, 18:24 UTC 200

Representation Learning — Google

https://www.google.co.in/alerts/feeds/05832220720342067762/1758013403…

146 items Polled 22 Sep, 18:25 UTC 200

Reinforcement Learning — Google

https://www.google.co.in/alerts/feeds/05832220720342067762/1720175169…

401 items Polled 22 Sep, 18:25 UTC 200

Generative AI — Google

https://www.google.co.in/alerts/feeds/05832220720342067762/7811591585…

401 items Polled 22 Sep, 18:25 UTC 200

Multimodal AI — Google

https://www.google.co.in/alerts/feeds/05832220720342067762/9568555102…

401 items Polled 22 Sep, 18:25 UTC 200

Mechanistic Interpretability — Google

https://www.google.co.in/alerts/feeds/05832220720342067762/8541059511…

33 items Polled 22 Sep, 18:25 UTC 200

RLHF — Google

https://www.google.co.in/alerts/feeds/05832220720342067762/7811591585…

32 items Polled 22 Sep, 18:25 UTC 200

Feeds are configured through the LEARN_FEEDS environment variable, so new sources can be added without a code change. Each poll sends the stored ETag and Last-Modified headers, so an unchanged feed answers 304 and costs the publisher nothing.