Tootfinder

discogs_genre: Discogs artist affiliations
Two bipartite networks of the affiliations between musical artists and either musical genres or musical "styles," as given in the discogs.com database. An edge indicates that a given artist was involved in a production of a particular genre or style. The date of this snapshot is uncertain.
This network has 1754838 nodes and 19033891 edges.
Tags: Informational, Relatedness, Unweighted

Designing efficient interventions for pre-disease states using control theory
Makito Oku
https://arxiv.org/abs/2507.18269 https://arxiv.org/pdf/2507.18269

Designing efficient interventions for pre-disease states using control theory
To extend healthy life expectancy in an aging society, it is crucial to prevent various diseases at pre-disease states. Although dynamical network biomarker theory has been developed for pre-disease detection, mathematical frameworks for pre-disease treatment have not been well established. Here I propose a control theory-based approach for pre-disease treatment, named Markov chain sparse control (MCSC), where time evolution of a probability distribution on a Markov chain is described as a disc…

California has already reported more measles cases this year than in all of 2024,
a worrisome development that comes as the nation is suffering its largest outbreak of the super-infectious disease in decades.
The extent of the national outbreak has rocketed measles from a back-of-mind issue
— one rarely, if ever, encountered by a whole generation of Americans
— to a pressing public health concern.
“Measles is completely preventable,”
Dr. Elizabeth Hudso…

Measles cases are on the rise in California
California has already reported more measles cases this year than in all of 2024, a worrisome development that comes as the nation is suffering its largest outbreak of the super-infectious disease in decades.

An Agentic System for Rare Disease Diagnosis with Traceable Reasoning
Weike Zhao, Chaoyi Wu, Yanjie Fan, Xiaoman Zhang, Pengcheng Qiu, Yuze Sun, Xiao Zhou, Yanfeng Wang, Ya Zhang, Yongguo Yu, Kun Sun, Weidi Xie
https://arxiv.org/abs/2506.20430

An Agentic System for Rare Disease Diagnosis with Traceable Reasoning
Rare diseases collectively affect over 300 million individuals worldwide, yet timely and accurate diagnosis remains a pervasive challenge. This is largely due to their clinical heterogeneity, low individual prevalence, and the limited familiarity most clinicians have with rare conditions. Here, we introduce DeepRare, the first rare disease diagnosis agentic system powered by a large language model (LLM), capable of processing heterogeneous clinical inputs. The system generates ranked diagnostic…

Multiple people have been stabbed at a Walmart in Michigan and a suspect is in custody (Associated Press)
https://apnews.com/article/walmart-stabbing-michigan-traverse-city-7d31d22005921a90e54c813a563c2457
http://www.memeorandum.com/250726/p46#a250726p46

I found the discus to be challenging because of the busy net in the background but you see people throwing can look like Greek statues so I want to give it another try
#sports #photo #photography…

While the idea that war isn't endlessly circular, but rather can be overcome and cured like disease or famine, may to some appear naively hopeful, it makes our world seem one shade less dark.

Learning from Anatomy: Supervised Anatomical Pretraining (SAP) for Improved Metastatic Bone Disease Segmentation in Whole-Body MRI
Joris Wuts, Jakub Ceranka, Nicolas Michoux, Fr\'ed\'eric Lecouvet, Jef Vandemeulebroucke
https://arxiv.org/abs/2506.19590

Learning from Anatomy: Supervised Anatomical Pretraining (SAP) for Improved Metastatic Bone Disease Segmentation in Whole-Body MRI
The segmentation of metastatic bone disease (MBD) in whole-body MRI (WB-MRI) is a challenging problem. Due to varying appearances and anatomical locations of lesions, ambiguous boundaries, and severe class imbalance, obtaining reliable segmentations requires large, well-annotated datasets capturing lesion variability. Generating such datasets requires substantial time and expertise, and is prone to error. While self-supervised learning (SSL) can leverage large unlabeled datasets, learned generi…

https://blog.csdn.net/wuShiJingZuo/article/details/139601073