Results 141 to 150 of about 822,176 (252)

Integrating feature importance techniques and causal inference to enhance early detection of heart disease. [PDF]

PLoS One
Arzanipour A.
europepmc   +1 more source

Time series causal relationships discovery through feature importance and ensemble models. [PDF]

Sci Rep, 2023
Castro M, Mendes Júnior PR, Soriano-Vargas A, de Oliveira Werneck R, Moreira Gonçalves M, Lusquino Filho L, Moura R, Zampieri M, Linares O, Ferreira V, Ferreira A, Davólio A, Schiozer D, Rocha A.   +13 more
europepmc   +1 more source

Gut microbiome and aging—A dynamic interplay of microbes, metabolites, and the immune system

FEBS Letters, EarlyView.
Age‐dependent shifts in microbial communities engender shifts in microbial metabolite profiles. These in turn drive shifts in barrier surface permeability of the gut and brain and induce immune activation. When paired with preexisting age‐related chronic inflammation this increases the risk of neuroinflammation and neurodegenerative diseases.
Aaron Mehl, Eran Blacher
wiley   +1 more source

Correction: Optimizing C-TIRADS for sub-centimeter thyroid nodules using machine learning-derived feature importance. [PDF]

Front Endocrinol (Lausanne)
Guo D, Lin Z, Wang J, Liao X, Huang H, Zhai Y, Chen Z.   +6 more
europepmc   +1 more source

Relationship between prediction accuracy and feature importance reliability: An empirical and theoretical study. [PDF]

Neuroimage, 2023
Chen J, Ooi LQR, Tan TWK, Zhang S, Li J, Asplund CL, Eickhoff SB, Bzdok D, Holmes AJ, Yeo BTT.   +9 more
europepmc   +1 more source

Valosin‐containing protein counteracts ATP‐driven dissolution of FUS condensates through its ATPase activity in vitro

FEBS Letters, EarlyView.
Biomolecular condensates formed by fused in sarcoma (FUS) are dissolved by high ATP concentrations yet persist in cells. Using a reconstituted system, we demonstrate that valosin‐containing protein (VCP), an AAA+ ATPase, counteracts ATP‐driven dissolution of FUS condensates through its D2 ATPase activity.
Hitomi Kimura, Shin‐ichi Tate, Kyota Yasuda   +2 more
wiley   +1 more source

Optimizing C-TIRADS for sub-centimeter thyroid nodules using machine learning-derived feature importance. [PDF]

Front Endocrinol (Lausanne)
Guo D, Lin Z, Wang J, Liao X, Huang H, Zhai Y, Chen Z.   +6 more
europepmc   +1 more source

Diversity and complexity in neural organoids

FEBS Letters, EarlyView.
Neural organoid research aims to expand genetic diversity on one side and increase tissue complexity on the other. Chimeroids integrate multiple donor genomes within single organoids. Self‐organising multi‐identity organoids, exogenous cell seeding, or enforced assembly of region‐specific organoids contribute to tissue complexity.
Ilaria Chiaradia, Madeline A. Lancaster
wiley   +1 more source

Topological embedding and directional feature importance in ensemble classifiers for multi-class classification. [PDF]

Comput Struct Biotechnol J
Rocha Liedl E, Yassin SM, Kasapi M, Posma JM.   +3 more
europepmc   +2 more sources

Simultaneous prediction of early and delayed mortality in burn patients: a comparative machine learning analysis of feature importance in a single-center retrospective study. [PDF]

BMC Med Inform Decis Mak
Motamedi M, Moallemkolaei NM, Hesamirostami M, Ghorbani M, Arani LS.   +4 more
europepmc   +1 more source