Results 181 to 190 of about 278,453 (275)

Toward Predictable Nanomedicine: Current Forecasting Frameworks for Nanoparticle–Biology Interactions

Advanced Intelligent Discovery, EarlyView.
Predictive models successfully screen nanoparticles for toxicity and cellular uptake. Yet, complex biological dynamics and sparse, nonstandardized data limit their accuracy. The field urgently needs integrated artificial intelligence/machine learning, systems biology, and open‐access data protocols to bridge the gap between materials science and safe ...
Mariya L. Ivanova, Michael Nicholls, Nicola Russo, Gueorgui Mihaylov, Konstantin Nikolic   +4 more
wiley   +1 more source

Radiochemotherapy for salivary gland adenoid cystic carcinoma: survival assessment through a retrospective study exploiting real-world data extracted from data warehouse. [PDF]

ESMO Real World Data Digit Oncol
Cavalieri S, Lombardi Stocchetti B, Crippa N, Silvestri C, Villa C, Ghelardi F, Baili P, Bonfarnuzzo S, Cavallo I, Iacovelli NA, Franceschini M, Filippi AR, Orlandi E, Deganello A, Cristofaro V, Bergamini C, Alfieri S, Nuzzolese I, Colombo E, Ottini A, Calareso G, Quattrone P, Licitra L.   +22 more
europepmc   +1 more source

Cell Segmentation Beyond 2D—A Review of the State‐of‐the‐Art

Advanced Intelligent Discovery, EarlyView.
Cell segmentation underpins many biological image analysis tasks, yet most deep learning methods remain limited to 2D despite the inherently 3D nature of cellular processes. This review surveys segmentation approaches beyond 2D, comparing 2.5D and fully 3D methods, analyzing 31 models and 32 volumetric datasets, and introducing a unified reference ...
Fabian Schmeisser, Haseeb Muhammad, Junaid Younas, Gillian Lovell, Bianca Migliori, Andreas Dengel, Sheraz Ahmed   +6 more
wiley   +1 more source

Feasibility of automated surveillance of implantable devices in orthopaedics via clinical data warehouse: the Studio study. [PDF]

BMC Med Inform Decis Mak
Ansoborlo M, Salpétrier C, Nail LL, Herbet J, Cuggia M, Rosset P, Grammatico-Guillon L.   +6 more
europepmc   +1 more source

Interpretability and Representability of Commutative Algebra, Algebraic Topology, and Topological Spectral Theory for Real‐World Data

Advanced Intelligent Discovery, EarlyView.
This article investigates how persistent homology, persistent Laplacians, and persistent commutative algebra reveal complementary geometric, topological, and algebraic invariants or signatures of real‐world data. By analyzing shapes, synthetic complexes, fullerenes, and biomolecules, the article shows how these mathematical frameworks enhance ...
Yiming Ren, Guo‐Wei Wei
wiley   +1 more source

Retrospective analysis of US veterans with inclusion body myositis: initial findings from the Veterans Affairs Corporate Data Warehouse. [PDF]

Mil Med Res
Liarski VM.
europepmc   +1 more source

Majority‐Voting Overlapping Method for Error Correction in DNA Data Storage

Advanced Intelligent Discovery, EarlyView.
We propose an overlapping‐based majority‐voting method for DNA data storage error correction. By aligning multiple reads and choosing the most frequent base per position, it suppresses substitution errors without prior models. Validated on synthetic and real sequencing data, it achieves high‐fidelity, scalable, and cost‐effective reconstruction ...
Thi Bich Ngoc Nguyen, Seongjun Seo, Anshula Tandon, Nguyen Kim Uyen, Thi Hong Nhung Vu, Sung Ha Park   +5 more
wiley   +1 more source

Machine Learning Driven Inverse Design of Broadband Acoustic Superscattering

Advanced Intelligent Discovery, EarlyView.
Multilayer acoustic superscatterers are designed using machine learning to achieve broadband superscattering and strong sound insulation. By incorporating a weighted mean absolute error into the loss function, the forward and inverse neural networks accurately map structural parameters to spectral responses.
Lijuan Fan, Xiangliang Zhang, Ying Wu
wiley   +1 more source

Clinical data warehouse analysis of clinical laboratory test results of Korean healthy volunteers: does "not clinically significant" range of healthy volunteers need modification? [PDF]

Transl Clin Pharmacol
Kim CJ, Kim TD, Park YC, Jung JG, Sunwoo J, Hong JH.   +5 more
europepmc   +1 more source

RAMS: Residual‐Based Adversarial‐Gradient Moving Sample Method for Scientific Machine Learning in Solving Partial Differential Equations

Advanced Intelligent Discovery, EarlyView.
We propose a residual‐based adversarial‐gradient moving sample (RAMS) method for scientific machine learning that treats samples as trainable variables and updates them to maximize the physics residual, thereby effectively concentrating samples in inadequately learned regions.
Weihang Ouyang, Min Zhu, Wei Xiong, Si‐Wei Liu, Lu Lu   +4 more
wiley   +1 more source