Large‐Scale Machine Learning to Screen for Small‐Molecule Senolytics
A consistent workflow underpins all experiments in this study. A dedicated model‐selection dataset first identifies optimal hyperparameters for each algorithm. Models are then trained and rigorously evaluated on independent sets of molecules using the senolytic ratio SR. Comprehensive hyperparameter exploration across SMILES representations, task types,
Alexis Dougha +2 more
wiley +1 more source
Bayesian Youden index for algorithmic evaluation under class imbalance: mathematical foundations with applications to insulin resistance and diabetes progression. [PDF]
Darghan A +5 more
europepmc +1 more source
Materials informatics and autonomous experimentation are transforming the discovery of organic molecular crystals. This review presents an integrated molecule–crystal–function–optimization workflow combining machine learning, crystal structure prediction, and Bayesian optimization with robotic platforms.
Takuya Taniguchi +2 more
wiley +1 more source
Editorial Comment on "From Test Accuracy to Clinical Risk Interpretation: A Bayesian Perspective on Pre-Biopsy Biomarkers". [PDF]
Hatakeyama S.
europepmc +1 more source
Artificial intelligence is redefining network pharmacology (NP). By integrating knowledge graph engineering, geometric deep learning, multiomics anchoring, and generative reasoning, AI‐driven NP (AI‐NP) transforms static target mapping into dynamic, predictive modeling.
Cong Wang +9 more
wiley +1 more source
Modeling conditional dependencies between recidivism and cognitive emotion regulation strategies among prisoners using a Bayesian network with interpretable summary indexes. [PDF]
Choi Y, Cho G.
europepmc +1 more source
We present CatTransVAE, a catalyst‐specialized chemical language model (CLM) built on a transformer variational autoencoder (VAE), developed through pretraining on general compounds followed by fine‐tuning on diverse catalyst databases. A template‐guided generation framework is introduced to enable controlled catalyst design under structural ...
Apakorn Kengkanna, Masahito Ohue
wiley +1 more source
Unveiling the Aha! moment: A computational account of insight in active inference. [PDF]
Doulfoukar Y, Pezzulo G, Stuyck H.
europepmc +1 more source
Crystal Structure Prediction of Inorganic Materials: A Benchmark and Modern Evaluation
Predicting a crystal’s structure from composition alone is a long‐standing challenge in materials discovery. The CSP180 benchmark of 180 inorganic crystals evaluates thirteen crystal structure prediction algorithms requiring no density functional theory (DFT) against DFT‐based baselines across twelve metrics.
Lai Wei +9 more
wiley +1 more source
Assessing the impact of AI-enabled BIM digital twins on construction risks: a Bayesian Network of Jordanian expert beliefs. [PDF]
Albtoush F +3 more
europepmc +1 more source

