Results 131 to 140 of about 117,341 (257)

Natural language processing to develop a standardized lexicon for precision medicine in oncology. [PDF]

J Manag Care Spec Pharm
Wang T, Tsai K, Kheloussi SS, McCormick D, Pawloski PA.   +4 more
europepmc   +1 more source

The Interoperability Challenge in DFT Workflows Across Implementations

Advanced Intelligent Discovery, EarlyView.
Interoperability and cross‐validation remain major challenges in the computational materials science. In this work, we introduce a common input/output standard that enables internal translation across multiple workflow managers—AiiDA, PerQueue, Pipeline Pilot, and SimStack—while producing results in a unified schema.
Simon K. Steensen, Tushar Singh Thakur, Manuel Dillenz, Johan M. Carlsson, Celso R. C. Rêgo, Eibar Flores, Hamidreza Hajiyani, Felix Hanke, Juan María García Lastra, Wolfgang Wenzel, Nicola Marzari, Tejs Vegge, Giovanni Pizzi, Ivano E. Castelli   +13 more
wiley   +1 more source

Domain-informed density extraction for robust mental health classification of long social media posts. [PDF]

Front Artif Intell
Hammad R, Rababah S.
europepmc   +1 more source

When Biology Meets Medicine: A Perspective on Foundation Models

Advanced Intelligent Discovery, EarlyView.
Artificial intelligence, and foundation models in particular, are transforming life sciences and medicine. This perspective reviews biological and medical foundation models across scales, highlighting key challenges in data availability, model evaluation, and architectural design.
Kunying Niu, Yuxing Wang, Limin Zou, Jing Huang   +3 more
wiley   +1 more source

Indeterminate CT reporting of adult acute appendicitis: radiologist versus lexicon-based diagnostic certainty. [PDF]

Insights Imaging
Siriphiphatcharoen P, Kaewlai R, Tongsai S, Chatpuwaphat J, Thiravit S, Wattanakul P, Thaisuriyo P, Noppakunsomboon N.   +7 more
europepmc   +1 more source

MolMiner: Toward Controllable, Three‐Dimensional‐Aware, Fragment‐Based Molecular Design

Advanced Intelligent Discovery, EarlyView.
MolMiner is a fragment‐based, geometry‐aware, and order‐agnostic generative model for molecular design with strong inductive biases. Using symmetry‐aware fragment assembly, dynamic three‐dimensional geometry, and multi‐property conditioning, MolMiner enables interpretable and controllable molecular generation.
Raul Ortega‐Ochoa, Tejs Vegge, Jes Frellsen   +2 more
wiley   +1 more source

Differential linguistic patterns across Rorschach, TAT, and SCT in individuals with PTSD. [PDF]

Eur J Psychotraumatol
Ahn H, Hong JS, Lee SH, Han DH.
europepmc   +1 more source

Accelerating the Discovery of Proton Conducting Electrolytes via Machine Learning‐Enabled Literature Mining

Advanced Intelligent Discovery, EarlyView.
An end‐to‐end knowledge discovery framework is established to automate high‐precision property extraction from small, specialized literature corpora. Utilizing a domain‐specific bidirectional encoder representation from a transformer model and data augmentation, the system accurately extracts and structures electrolyte performance data, ultimately ...
Gaheun Shin, Seongho Lee, Seulchan Kim, Ho‐Il Ji, Joonhee Kang   +4 more
wiley   +1 more source

Harmonizing Multi-Institutional Clinical Documentation Using Natural Language Processing in Neurofibromatosis Type 1. [PDF]

Neurol Clin Pract
Morris SM, Kaster L, Amagai S, Raski C, Regan-Fendt K, Luo Y, Rosenman M, Prada CE, Listernick R, Payne PRO, Gutmann DH, Gupta A.   +11 more
europepmc   +1 more source

From Word2Vec to Transformers: Text‐Derived Composition Embeddings for Filtering Combinatorial Electrocatalysts

Advanced Intelligent Discovery, EarlyView.
With the downstream filter held fixed, text‐derived composition representations produce distinct screening outcomes across 14 electrocatalyst libraries. Embedding model and composition encoding control the trade‐off between candidate reduction and preservation of the best measured current.
Lei Zhang, Markus Stricker
wiley   +1 more source