Results 51 to 60 of about 76,023 (254)
Explainable Artificial Intelligence (XAI)
The field of explainable artificial intelligence (XAI) advances techniques, processes, and strategies that provide explanations for the predictions, recommendations, and decisions of opaque and complex machine learning systems. Increasingly academic libraries are providing library users with systems, services, and collections created and delivered by ...
openaire +3 more sources
Multiple Explainable Approaches to Predict the Risk of Stroke Using Artificial Intelligence
Stroke occurs when a brain’s blood artery ruptures or the brain’s blood supply is interrupted. Due to rupture or obstruction, the brain’s tissues cannot receive enough blood and oxygen. Stroke is a common cause of mortality among older people.
Susmita S +5 more
doaj +1 more source
ABSTRACT Objective To investigate the value of constructing models based on habitat radiomics and pathomics for predicting the risk of progression in high‐grade gliomas. Methods This study conducted a retrospective analysis of preoperative magnetic resonance (MR) images and pathological sections from 72 patients diagnosed with high‐grade gliomas (52 ...
Yuchen Zhu +14 more
wiley +1 more source
The demands of controlling when meeting cutting-edge technology are quite high given its underlying principles, its prospective character, flexibility, but also the desire for transparency, ethics, and responsibility.
Luana COSĂCESCU
doaj +1 more source
Multidimensional Profiling of MRI‐Negative Temporal Lobe Epilepsy Uncovers Distinct Phenotypes
ABSTRACT Objective Although hippocampal sclerosis (TLE‐HS) represents the most frequent cause of temporal lobe epilepsy (TLE), up to 30% of patients show no lesion on visual MRI inspection (TLE‐MRIneg). These cases pose diagnostic and therapeutic challenges and are underrepresented in surgical series.
Alice Ballerini +28 more
wiley +1 more source
In recommender systems, leveraging user interaction history as sequential information has recently led to significant performance improvements. However, in many online services, user interactions are often grouped into sessions that inherently share user
Jinseok Seol, Youngrok Ko, Sang-Goo Lee
doaj +1 more source
Objective We developed a novel electronic health record sidecar application to visualize key rheumatoid arthritis (RA) outcomes, including disease activity, physical function, and pain, via a patient‐facing graphical interface designed for use during outpatient visits (“RA PRO dashboard”).
Gabriela Schmajuk +16 more
wiley +1 more source
Retractions in Rheumatology: Trends, Causes, and Implications for Research Integrity
Objective We aimed to describe the trends and main reasons for study retraction in rheumatology literature. Methods We reviewed the Retraction Watch database to identify retracted articles in rheumatology. We recorded the main study characteristics, authors’ countries, reasons for retraction, time from publication to retraction, and trends over time ...
Anna Maria Vettori, Michele Iudici
wiley +1 more source
Harnessing Fungal Biowelding for Constructing Mycelium‐Engineered Materials
Mycelium‐bound composites (MBCs) offer low‐carbon alternatives for construction, yet interfacial bonding remains a critical challenge. This review examines fungal biowelding as a biocompatible adhesive, elucidating mycelium‐mediated interfacial mechanisms and their role in material assembly. Strategies to optimize biowelding are discussed, highlighting
Xue Brenda Bai +2 more
wiley +1 more source
Fully Interpretable Deep Learning Model Using IR Thermal Images for Possible Breast Cancer Cases
Breast cancer remains a global health problem requiring effective diagnostic methods for early detection, in order to achieve the World Health Organization’s ultimate goal of breast self-examination. A literature review indicates the urgency of improving
Yerken Mirasbekov +6 more
doaj +1 more source

