Results 141 to 150 of about 1,001,459 (337)

Conversion Therapy for cT4b and M1 Esophageal Squamous Cell Carcinoma: A Comprehensive Systematic Review

Annals of Gastroenterological Surgery, EarlyView.
We systematically reviewed conversion therapy for esophageal squamous cell carcinoma and propose a response‐based treatment strategy for cT4b and M1 disease. For cT4b, we emphasize definitive chemoradiotherapy with timed re‐evaluation and selective salvage or chemoselection to surgery; for M1, conversion is reserved for limited‐burden responders with ...
Eisuke Booka, Hiroya Takeuchi
wiley   +1 more source

AI‐Enhanced Surface‐Enhanced Raman Scattering for Accurate and Sensitive Biomedical Sensing

Advanced Intelligent Discovery, EarlyView.
AI‐SERS advances spectral interpretation with greater precision and speed, enhancing molecular detection, biomedical analysis, and imaging. This review explores its essential contributions to biofluid analysis, disease identification, therapeutic agent evaluation, and high‐resolution biomedical imaging, aiding diagnostic decision‐making.
Seungki Lee, Rowoon Park, Ho Sang Jung
wiley   +1 more source

Comparative Analysis of Deep Learning-Based Feature Extractors for Change Detection in Automotive Radar Maps

IEEE Access
The Siamese network architecture has been applied by deep learning practitioners to find similarities between images. In the domain of autonomous driving, this network configuration has recently gained attention for solving the change detection task ...
Harihara Bharathy Swaminathan, Aron Sommer, Uri Iurgel, Andreas Becker, Martin Atzmueller   +4 more
doaj   +1 more source

What to Make and How to Make It: Combining Machine Learning and Statistical Learning to Design New Materials

Advanced Intelligent Discovery, EarlyView.
Combining machine learning and probabilistic statistical learning is a powerful way to discover and design new materials. A variety of machine learning approaches can be used to identify promising candidates for target applications, and causal inference can help identify potential ways to make them a reality.
Jonathan Y. C. Ting, Amanda S. Barnard
wiley   +1 more source

Opposite Information Annotation on ‘Word List by Semantic Principles’

, 2021
Sachi Kato, Masayuki Asahara, Nanami Moriyama, Asami Ogiwara, Makoto Yamazaki   +4 more
openalex   +2 more sources

Named Entity Recognition Models for Machine Learning Interatomic Potentials: A User‐Centric Approach to Knowledge Extraction from Scientific Literature

Advanced Intelligent Discovery, EarlyView.
Named entity recognition pipeline for knowledge extraction from scientific literature. Machine learning interatomic potential (MLIP) is an emerging technique that has helped achieve molecular dynamics simulations with unprecedented balance between efficiency and accuracy. Recently, the body of MLIP literature has been growing rapidly, which propels the
Bowen Zheng, Grace X. Gu
wiley   +1 more source

Occupational health assessment summary designed for semantic interoperability

, 2023
Evgeniy Krastev, Dimitar Tcharaktchiev, Petko Kovachev, Simeon Abanos   +3 more
openalex   +1 more source

Harnessing Large Language Models to Advance Microbiome Research: From Sequence Analysis to Clinical Applications

Advanced Intelligent Discovery, EarlyView.
Large language models are transforming microbiome research by enabling advanced sequence profiling, functional prediction, and association mining across complex datasets. They automate microbial classification and disease‐state recognition, improving cross‐study integration and clinical diagnostics.
Jieqi Xing, He Wang, Yangyang Sun, Xiaoquan Su, Shunyao Wu   +4 more
wiley   +1 more source

TSINet: A Semantic and Instance Segmentation Network for 3D Tomato Plant Point Clouds [PDF]

Shanshan Ma, Xu Lu, Liang Zhang
openalex   +1 more source

A SEMANTIC ANALYSIS OF LOCATIVE EXPRESSIONS: THE PROBLEM OF INTRANSITIVITY IN PREPOSITIONS [PDF]

, 2004
Ana Ibáñez Moreno
openalex   +1 more source