# Muscle Atrophy ML ensemble an SHAP xAi paper worth a read **URL:** \ **Category:** AI/ML AWG Topics\ **Tags:** interesting, paper\ **Created:** [February 25, 2026, 6:08am UTC](https://awg.osdr.space/t/muscle-atrophy-ml-ensemble-an-shap-xai-paper-worth-a-read/3917 "2026-02-25T06:08:51Z")\ **Posts on this page:** 3\ **Page:** 1
**Author:** ![rtscott2001](https://sea1.discourse-cdn.com/flex001/user_avatar/awg.osdr.space/rtscott2001/32/5_2.png) [@rtscott2001](https://awg.osdr.space/u/rtscott2001)\ **Post date:** [February 25, 2026, 6:08am UTC](https://awg.osdr.space/t/muscle-atrophy-ml-ensemble-an-shap-xai-paper-worth-a-read/3917/1 "2026-02-25T06:08:51Z")
While not an OSDR data mining paper, the study is space health relevant, and does have to deal with small N, and interesting approach with the ensemble voting and SHAP explainable ML Mummaneni, S., Rayalavarapu, T. A. K., Kadimi, R., & Shaik, L. B. (2026). Classification of Simulated-Microgravity-Induced Muscle Atrophy Using Transcriptomic Data and Ensemble Learning. _IAENG International Journal of Applied Mathematics_, _56_(1). Paper: [https://www.iaeng.org/IJCS/issues\_v53/issue\_1/IJCS\_53\_1\_16.pdf](https://www.iaeng.org/IJCS/issues_v53/issue_1/IJCS_53_1_16.pdf) They mined this GEO dataset: [https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE148152](https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE148152) ![IMG_1685](https://us1.discourse-cdn.com/flex001/uploads/osdr/original/2X/0/061d1709be85feb30dd5cf33a6a1c2a48582fb0f.jpeg) [@AIMLawg](https://awg.osdr.space/groups/aimlawg) @james.casaletto @anna.lewkowicz @lauren.sanders @vaishnavi.nagesh @asaravia ---
**Author:** ![amaanarif25](https://sea1.discourse-cdn.com/flex001/user_avatar/awg.osdr.space/amaanarif25/32/3323_2.png) [@amaanarif25](https://awg.osdr.space/u/amaanarif25)\ **Post date:** [February 25, 2026, 10:03am UTC](https://awg.osdr.space/t/muscle-atrophy-ml-ensemble-an-shap-xai-paper-worth-a-read/3917/2 "2026-02-25T10:03:44Z")
Really interesting work on simulated microgravity and small-N transcriptomics. I recently completed a research study on neurological disease using transcriptomics data, similar to what was done in the paper (currently without an ML model), and this paper gave me strong ideas, especially the ensemble voting and SHAP explainability. Thank you for sharing this valuable resource. ---
**Author:** ![rtscott2001](https://sea1.discourse-cdn.com/flex001/user_avatar/awg.osdr.space/rtscott2001/32/5_2.png) [@rtscott2001](https://awg.osdr.space/u/rtscott2001)\ **Post date:** [February 25, 2026, 3:37pm UTC](https://awg.osdr.space/t/muscle-atrophy-ml-ensemble-an-shap-xai-paper-worth-a-read/3917/3 "2026-02-25T15:37:24Z")
Very cool @amaanarif25 The only reason I found it was they cited a muscle study I was part of, and also inclding AWG members collaborating, looking at RR data from 2022-23: Li, K., Desai, R., Scott, R.T., Steele, J.R., Machado, M., Demharter, S., Hoarfrost, A., Braun, J.L., Fajardo, V.A., Sanders, L.M. and Costes, S.V. Explainable machine learning identifies multi-omics signatures of muscle response to spaceflight in mice. _npj Microgravity_ **9** , 90 (2023). [https://doi.org/10.1038/s41526-023-00337-5](https://doi.org/10.1038/s41526-023-00337-5) Though one part of the paper in the main post thread which makes me very sad is that there MUST be some sort of AI Slop chatgpt bull crap used by the authors (and makes me question the rest of the content a bit) as they reference our above paper with hallucinated authors as: ![image](https://us1.discourse-cdn.com/flex001/uploads/osdr/original/2X/7/77e6fd69213b8b7b5dcbd1429089b211e8355cd7.png) 😑 ie, no Estella nor Roberts… I guess at least Kevin Li was mentioned! @lauren.sanders @vfajardo @joel.steele @svcostes There will a joint educational series between the AWG, OSMED, and IIAS starting soon, and one of the topics will be the right way and the wrong ways to use generative AI tools and science Ethics. Other topics will be on predatory journals, as well as peer review.