Results 101 to 110 of about 59,770 (264)

Decoding Naturalistic Episodic Memory with Artificial Intelligence and Brain‐Machine Interface

open access: yesAdvanced Science, EarlyView.
Episodic memory weaves together what, where, and when of experience into a personal narrative. Cutting‐edge AI models may decode this intricate process in real‐life settings, revealing how neural activity encodes naturalistic memories. By merging AI with brain–machine interfaces, researchers are edging closer to mapping and even engineering memory ...
Dong Song
wiley   +1 more source

Multimodal deep learning for dementia classification using text and audio

open access: yesScientific Reports
Dementia is a progressive neurological disorder that affects the daily lives of older adults, impacting their verbal communication and cognitive function.
Kaiying Lin, Peter Y. Washington
doaj   +1 more source

Integrating Spatial Proteogenomics in Cancer Research

open access: yesAdvanced Science, EarlyView.
Xx xx. ABSTRACT Background: Spatial proteogenomics marks a paradigm shift in oncology by integrating molecular analysis with spatial information from both spatial proteomics and other data modalities (e.g., spatial transcriptomics), thereby unveiling tumor heterogeneity and dynamic changes in the microenvironment.
Yida Wang   +13 more
wiley   +1 more source

Unsupervised Hierarchical Symbolic Regression for Interpretable Property Modeling in Complex Multi‐Variable Systems

open access: yesAdvanced Science, EarlyView.
UHSR translates complex chemical behavior into clear and explainable equations. Applied to thin‐layer chromatography, it automatically uncovers the mathematical rules linking a molecule's structure to its polarity. This approach matches the accuracy of advanced AI while providing interpretable results, earning greater trust from chemists. The method is
Siyu Lou   +4 more
wiley   +1 more source

Machine Learning-Based Hate Speech Detection in the Kazakh Language

open access: yesResearch in Language
Modern text data processing and classification methods require extensive use of machine learning and neural networks. Categorizing text into different classes has become a crucial task in many fields.
Milana Bolatbek   +2 more
doaj   +1 more source

Rapid Proteome‐Wide Discovery of Protein–Protein Interactions With ppIRIS

open access: yesAdvanced Science, EarlyView.
ppIRIS is a lightweight deep learning framework for proteome‐wide protein–protein interaction prediction directly from sequence. By fusing evolutionary and structural embeddings with a regularized Siamese architecture, ppIRIS achieves state‐of‐the‐art accuracy across species, enables minute‐scale screening, and reveals biologically validated bacterial ...
Luiz Felipe Piochi   +4 more
wiley   +1 more source

Business text classification with imbalanced data and moderately large label spaces for digital transformation

open access: yesApplied Network Science
Digital transformation refers to an organization’s use of digital technology to improve its products, services, and operations, aligning them with evolving business requirements.
Muhammad Arslan, Christophe Cruz
doaj   +1 more source

A Scalable Framework for Comprehensive Typing of Polymorphic Immune Genes from Long‐Read Data

open access: yesAdvanced Science, EarlyView.
SpecImmune introduces a unified computational framework optimized for long‐read sequencing to resolve over 400 highly polymorphic immune genes. This scalable approach achieves high‐resolution typing, enabling the discovery of cross‐family co‐evolutionary networks and population‐specific diversity.
Shuai Wang   +5 more
wiley   +1 more source

Novel Multichannel Deep Learning Model for Arabic News Classification

open access: yesJordanian Journal of Computers and Information Technology
In the era of digital journalism, the classification of Arabic news presents a significant challenge due to the complex nature of the language and the vast diversity of content.
Imad Jamaleddyn   +2 more
doaj   +1 more source

Leveraging Artificial Intelligence and Large Language Models for Cancer Immunotherapy

open access: yesAdvanced Science, EarlyView.
Cancer immunotherapy faces challenges in predicting treatment responses and understanding resistance mechanisms. Artificial intelligence (AI) and machine learning (ML) offer powerful solutions for cancer immunotherapy in patient stratification, biomarker discovery, treatment strategy optimization, and foundation model development.
Xinchao Wu   +4 more
wiley   +1 more source

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