AI‐Driven Cancer Multi‐Omics: A Review From the Data Pipeline Perspective
The exponential growth of cancer multi‐omics data brings opportunities and challenges for precision oncology. This review systematically examines AI's role in addressing these challenges, covering generative models, integration architectures, Explainable AI for clinical trust, clinical applications, and key directions for clinical translation.
Shilong Liu, Shunxiang Li, Kun Qian
wiley +1 more source
Topological insights into breast cancer drugs: a QSPR approach using resolving topological indices. [PDF]
Pandeeswari E, Ravi Sankar J.
europepmc +1 more source
Uncertainty‐Guided Selective Adaptation Enables Cross‐Platform Predictive Fluorescence Microscopy
Deep learning models often fail when transferred to new microscopes. A novel framework overcomes this by selectively adapting the early layers governing low‐level image statistics, while freezing deep layers that encode morphology. This uncertainty‐guided approach enables robust, label‐free virtual staining across diverse systems, democratizing ...
Kai‐Wen K. Yang +9 more
wiley +1 more source
Applications of Sombor topological indices and entropy measures for QSPR modeling of anticancer drugs: a Python-based methodology. [PDF]
Kara Y +3 more
europepmc +1 more source
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
Prediction of suitable drug for keloid through analytic hierarchy process and topological indices. [PDF]
Janagi K +3 more
europepmc +1 more source
Artificial intelligence (AI) is reshaping autonomous mobile robot navigation beyond classical pipelines. This review analyzes how AI techniques are integrated into core navigation tasks, including path planning and control, localization and mapping, perception, and context‐aware decision‐making. Learning‐based, probabilistic, and soft‐computing methods
Giovanna Guaragnella +5 more
wiley +1 more source
DFT based structural modeling of chemotherapy drugs via topological indices and curvilinear regression. [PDF]
Saeed F, Idrees N, Imran M.
europepmc +1 more source
Material‐Based Intelligence: Autonomous Adaptation and Embodied Computation in Physical Substrates
This perspective formulates a unifying framework for Material‐Based Intelligence (MBI), defining the physical requirements for materials to achieve embodied action, active memory and embodied information processing through intrinsic nonequilibrium dynamics. The design of intelligent materials often draws parallels with the complex adaptive behaviors of
Vladimir A. Baulin +4 more
wiley +1 more source
Isolation and Reactivity of a Square‐Planar Trisamido Silane
We report the synthesis and comprehensive characterisation of a square‐planar Si(+IV) hydride supported by an unsymmetric, trianionic and dearomatised N,N,N‐pincer ligand. This system enables element–ligand cooperative reactivity as an alternative to silicon‐centred redox chemistry, illuminating a largely unexplored regime in high‐valent silicon ...
David M. J. Krengel +5 more
wiley +2 more sources

