Results 71 to 80 of about 5,831 (221)
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
Named entity resolution using automatically extracted semantic information
, 2022 8491One major problem in text mining and semantic retrieval is that detected entity mentions have to be assigned to the true underlying entity. The ambiguity of a name results from both the polysemy and synonymy problem, as the name of a unique entity ...
Paaß, Gerhard, Pilz, Anja
core
Advanced Intelligent Systems, EarlyView.OntoLogX is an autonomous AI agent that uses large language models to transform unstructured cyber security logs into ontology grounded knowledge graphs. By integrating retrieval augmented generation, iterative correction, and a light‐weight log ontology, OntoLogX produces semantically consistent intelligence that links raw log events to MITRE ATT & CK
Luca Cotti +4 more
wiley +1 more source
Xstainer: A Novel Virtual Staining Tool Powered by Advanced Deep Learning Techniques
Advanced Intelligent Systems, EarlyView.Xstainer is a deep learning–based virtual staining framework that converts hematoxylin and eosin‐stained whole slide images into multiple histochemical stains, including Masson's trichrome, Periodic acid‐Schiff, Jones methenamine silver, and Toluidine blue.
Fatma Nur Kinali +15 more
wiley +1 more source
Boosting for Named Entity Recognition
, 2002 This paper presents a system that applies boosting to the task of named-entity identification. The CoNLL-2002 shared task, for which the system is designed, is language-independent named-entity recognition.
Clear Water Bay +4 more
core
AI &Innovation, EarlyView.ABSTRACT The rapid advancement of large language model (LLM) technology is profoundly transforming the practice of social science research. Scholarly discussions on Artificial Intelligence (AI)'s role in social science research can be organised into three levels: AI as a research tool, AI as a methodological infrastructure and AI as a quasi‐cognitive ...
Jie Xiong
wiley +1 more source
STEM: stacked threshold-based entity matching for knowledge base generation [PDF]
, 2018 One of the major issues encountered in the generation of knowledge bases is the integration of data coming from a collection of heterogeneous data sources. A key essential task when integrating data instances is the entity matching.
Giuseppe Rizzo +2 more
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Developmental and Phenotypic Outcomes in Mild Phenylalanine Hydroxylase Deficiency
American Journal of Medical Genetics Part A, EarlyView.ABSTRACT Benign hyperphenylalaninemia (bHPA) is defined as elevated phenylalanine (Phe) levels remaining ≤ 360 μmol/L (6 mg/dL) and not requiring medical intervention. Individuals with bHPA may demonstrate a rise in their Phe levels > 360 μmol/L, effectively developing a mild PKU phenotype requiring therapy to prevent neurocognitive complications. This
Aaron Williams +8 more
wiley +1 more source
Dutch Named Entity Recognition using Classifier Ensembles [PDF]
, 2010 This paper explores the use of classifier ensembles for the task of named entity recognition (NER) on a Dutch dataset. Classifiers from 3 classification frameworks, namely memory-based learning (MBL), conditional random fields (CRF) and support vector ...
Desmet, Bart, Hoste, Véronique
core
, 2013 Training time and classification time of whole data set (4,037,099 pixels) using various classifiers on different cases based on ETM+ image unit:second.
Shijun Deng (436523) +9 more
core +1 more source