Results 131 to 140 of about 1,214,867 (285)
A unified ontological and explainable framework for decoding AI risks from news data
Scientific ReportsArtificial intelligence (AI) is rapidly permeating various aspects of human life, raising growing concerns about its associated risks. However, existing research on AI risks often remains fragmented—either limited to specific domains or focused solely on
Chuan Chen +6 more
doaj +1 more source
Explainable AI in the military domain
Ethics and Information TechnologyAbstractArtificial intelligence (AI) has become nearly ubiquitous in modern society, from components of mobile applications to medical support systems, and everything in between. In societally impactful systems imbued with AI, there has been increasing concern related to opaque AI, that is, artificial intelligence where it is unclear how or why certain
openaire +1 more source
New Directions for Adult and Continuing Education, EarlyView.ABSTRACT Advancing artificial intelligence (AI) has transformed learning and work, yet higher education and professional development programs have not systematically equipped learners for AI‐prevalent environments. This lack of preparation creates uncertainty regarding control, responsibility, trust, and accountability.
Moon‐Heum Cho, Jerusalem Merkebu
wiley +1 more source
An explainable AI model for power plant NOx emission control
In recent years, developing Artificial Intelligence (AI) models for complex system has become a popular research area. There have been several successful AI models for predicting the Selective Non-Catalytic Reduction (SNCR) system in power plants and ...
Kyprianidis, Konstantinos, +7 more
core +1 more source
Added Prognostic Value of EEG Reactivity in Comatose Patients Following Cardiac Arrest
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objectives To evaluate the added prognostic value of EEG reactivity for favorable outcome compared with background analysis during and after targeted temperature management (TTM). Methods Prospective observational cohort study of comatose post–cardiac arrest patients admitted to a single academic center between 2017 and 2022, all undergoing ...
Sarah Caroyer +11 more
wiley +1 more source
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objectives Acute kidney injury (AKI) is a common but often underrecognized complication in ischemic stroke patients undergoing mechanical thrombectomy, particularly among those with pre‐existing renal impairment. This study evaluated the incidence, risk factors, and clinical impact of AKI in this high‐risk population.
Michał Borończyk +10 more
wiley +1 more source
Screening Routine Clinical Notes for Epilepsy Surgery Candidates Using Large Language Models
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Epilepsy surgery is severely underutilized despite proven efficacy, with substantial under‐referral of eligible patients in routine clinical practice. This study evaluated the potential role of large language models (LLMs) as decision‐support tools for screening unstructured clinical notes to identify epilepsy surgery candidates and ...
Uriel Fennig +9 more
wiley +1 more source
A Two‐Stage Questionnaire and Actigraphy Screening for iRBD in a Multicenter Retrospective Cohort
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Isolated rapid‐eye‐movement sleep behavior disorder is a prodromal marker of synucleinopathies. However, most cases remain undiagnosed due to the insufficient predictive value of questionnaires and limited access to confirmatory video‐polysomnography. We assessed a two‐stage screening strategy combining a brief questionnaire on rapid‐
Caleb A. Massimi +17 more
wiley +1 more source
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Introduction/Objective Acute intracranial stenting during endovascular thrombectomy (EVT) for ischemic stroke requires intraprocedural antiplatelet therapy (APT) to maintain patency. However, the hemorrhagic risk of combining APT with intravenous thrombolysis (IVT) remains uncertain.
Aaron Rodriguez‐Calienes +75 more
wiley +1 more source
Explainable AI for Mixed Data Clustering
4262Clustering, an unsupervised machine learning approach, aims to find groups of similar instances. Mixed data clustering is of particular interest since real-life data often consists of diverse data types.
Amling, Jonas +4 more
core +1 more source