Computational modeling and optimized machine learning for multidrug solubility prediction in supercritical carbon dioxide.

Abu-Hamdeh NH, Hijji HH, Almitani KH

DOI: 10.3389/fmed.2026.1985801
Published: 2026
Container: Frontiers in medicine
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.3389/fmed.2026.1985801,
  title = {Computational modeling and optimized machine learning for multidrug solubility prediction in supercritical carbon dioxide.},
  author = {Abu-Hamdeh NH and Hijji HH and Almitani KH},
  year = {2026},
  journal = {Frontiers in medicine},
  doi = {10.3389/fmed.2026.1985801},
  url = {https://doi.org/10.3389/fmed.2026.1985801}
}

RIS

TY  - JOUR
TI  - Computational modeling and optimized machine learning for multidrug solubility prediction in supercritical carbon dioxide.
AU  - Abu-Hamdeh NH
AU  - Hijji HH
AU  - Almitani KH
PY  - 2026
JO  - Frontiers in medicine
DO  - 10.3389/fmed.2026.1985801
UR  - https://doi.org/10.3389/fmed.2026.1985801
ER  -

APA

NH, A., HH, H., & KH, A. (2026). Computational modeling and optimized machine learning for multidrug solubility prediction in supercritical carbon dioxide.. Frontiers in medicine. https://doi.org/10.3389/fmed.2026.1985801

Source records

pubmed · retrieved 2026-11-10T20:17:26.261Z
europe-pmc · retrieved 2026-11-10T20:17:26.269Z