Results 161 to 170 of about 10,759 (212)

AI‐Driven Cancer Multi‐Omics: A Review From the Data Pipeline Perspective

Advanced Intelligent Discovery, EarlyView.
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

Two years into an ongoing war: a six-wave prospective study of PTSD, depression, anxiety, and posttraumatic growth following the October 7, 2023, attack in Israel. [PDF]

EClinicalMedicine
Levi-Belz Y, Amsalem D, Groweiss Y, Blank C, Kohavi H, Neria Y.   +5 more
europepmc   +1 more source

Interpretable Machine Learning for Bandgap Prediction and Descriptor‐Guided Design Rules of Phosphates

Advanced Intelligent Discovery, EarlyView.
An explainable CatBoost model was trained to predict the bandgaps of 474 phosphate crystals based on composition and density descriptors. SHAP analysis identified two key variables—d‐electron‐count dispersion and atomic‐density dispersion—as the primary drivers of the model's predictions.
Wenhu Wang, Abudukadi Tudi, Ran An, Zhihua Yang   +3 more
wiley   +1 more source

A robust and versatile deep learning model for prediction of the arterial input function in dynamic small animal [¹⁸F] FDG PET imaging. [PDF]

EJNMMI Res
Salomonsen C, Luppino LT, Aspheim F, Wickstrøm K, Wetzer E, Kampffmeyer M, Berzaghi R, Sundset R, Jenssen R, Kuttner S.   +9 more
europepmc   +1 more source

Spatially Informed Feature Selection and Machine Learning in Matrix‐Assisted Laser Desorption/Ionization Imaging for Cohort‐Scale Molecular Tissue Phenomics in Glioblastoma

Advanced Intelligent Discovery, EarlyView.
Matrix‐assisted laser desorption/ionization imaging‐based identification of reliable small molecule markers across heterogeneous glioblastoma cohorts is challenging with intensity‐only methods. We present spatially informed feature selection (SIFS), a spatially informed framework that prioritizes molecules consistently colocalizing with histopathology.
Shad A. Mohammed, Denis Abu Sammour, Dirk C. Hoffmann, Philipp Sievers, Tobias Bausbacher, Melissa Hahn, Yasemin Ucal, Iris Mildenberger, Christiane A. Opitz, Stefan Schmidt, Michael Platten, Oliver Wasenmüller, Wolfgang Wick, Andreas von Deimling, Tobias Kessler, Carsten Hopf   +15 more
wiley   +1 more source

A surrogate endpoint-based provisional approval causal roadmap, illustrated by vaccine development. [PDF]

Biostatistics
Gilbert PB, Peng J, Han L, Lange T, Lu Y, Nie L, Shih MC, Waddy SP, Wiley K, Yann M, Zafari Z, Ghosh D, Follmann D, Juraska M, Díaz I.   +14 more
europepmc   +1 more source

Smart Bioinspired Material‐Based Actuators: Current Challenges and Prospects

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
This work gathers, in a review style, an extensive and comprehensive literature overview on the development of autonomous actuators based on synthetic materials, bringing together valuable knowledge from several studies. Furthermore, the article identifies the fundamental principles of actuation mechanisms and defines key parameters to address the size
Alejandro Palacios, Léon Chiriatti, Simon Poppinga, Thomas Speck, Vincent Le Houérou   +4 more
wiley   +1 more source

Machine Learning Models for Pancreatic Cancer Survival Prediction: A Multi-Model Analysis Across Stages and Treatments Using the Surveillance, Epidemiology, and End Results (SEER) Database. [PDF]

J Clin Med
Chakraborty A, Pant MD.
europepmc   +1 more source

Robust Reinforcement Learning Control Framework for a Quadrotor Unmanned Aerial Vehicle Using Critic Neural Network

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
Quadrotor unmanned aerial vehicle control is critical to maintain flight safety and efficiency, especially when facing external disturbances and model uncertainties. This article presents a robust reinforcement learning control scheme to deal with these challenges.
Yu Cai, Yefeng Yang, Tao Huang, Boyang Li   +3 more
wiley   +1 more source

Experimental Joint Estimation of Phase and Phase Diffusion Via Deterministic Bell Measurements. [PDF]

Adv Sci (Weinh)
Wang B, Mi M, Wang H, Xie Q, Zhang L.
europepmc   +1 more source