Results 51 to 60 of about 29,455 (191)

Survey of XAI in Digital Pathology [PDF]

, 2020
Artificial intelligence (AI) has shown great promise for diagnostic imaging assessments. However, the application of AI to support medical diagnostics in clinical routine comes with many challenges. The algorithms should have high prediction accuracy but also be transparent, understandable and reliable.
Milda Poceviciute, Gabriel Eilertsen, Claes Lundström   +2 more
openaire   +3 more sources

DEEP LEARNING-BASED MELANOMA CLASSIFICATION ENHANCED BY FRACTAL DIMENSION ANALYSIS

KPI Science News
Background. Melanoma is a malignant skin lesion that is prone to metastasize aggressively, leading to an almost guaranteed lethal outcome if left unchecked.
Vladyslav Nikitin, Valerii Danilov
doaj   +1 more source

Recent Advances in Explainable Artificial Intelligence for Magnetic Resonance Imaging

Diagnostics, 2023
Advances in artificial intelligence (AI), especially deep learning (DL), have facilitated magnetic resonance imaging (MRI) data analysis, enabling AI-assisted medical image diagnoses and prognoses.
Jinzhao Qian, Hailong Li, Junqi Wang, Lili He   +3 more
doaj   +1 more source

Old man at /Xai/xai.

, 1968
This man (name and master number?) was said to be the oldest living person in /Xai/xai. Estimated 90+ years.
Lee, Richard
core   +2 more sources

Actionable Learning Analytics: Predicting University Performance Levels with Interpretable Machine Learning

Journal on Efficiency and Responsibility in Education and Science
Higher education institutions need timely, explainable tools to identify students at risk of low performance on large-scale examinations and to guide targeted academic support strategies.
Enrique De La Hoz, Carlos Garcia-Yerena, Ingrid Torres-Rojas   +2 more
doaj   +1 more source

Demystifying XAI: Requirements for Understandable XAI Explanations

This paper establishes requirements for assessing the usability of Explainable Artificial Intelligence (XAI) methods, focusing on non-AI experts like healthcare professionals. Through a synthesis of literature and empirical findings, it emphasizes achieving optimal cognitive load, task performance, and task time in XAI explanations.
Jan Stodt, Christoph Reich, Martin Knahl
openaire   +2 more sources

Forms of understanding for XAI-Explanations

Cognitive Systems Research
revised ...
Hendrik Buschmeier, Heike M. Buhl, Friederike Kern, Angela Grimminger, Helen Beierling, Josephine Fisher, André Groß, Ilona Horwath, Nils Klowait, Stefan Lazarov, Michael Lenke, Vivien Lohmer, Katharina Rohlfing, Ingrid Scharlau, Amit Singh, Lutz Terfloth, Anna-Lisa Vollmer, Yu Wang, Annedore Wilmes, Britta Wrede   +19 more
openaire   +4 more sources

Intelligent explainable optical sensing on Internet of nanorobots for disease detection

Nanotechnology Reviews
Combining deep learning (DL) with nanotechnology holds promise for transforming key facets of nanoscience and technology. This synergy could pave the way for groundbreaking advancements in the creation of novel materials, devices, and applications ...
Mesgaribarzi Niusha, Djenouri Youcef, Belbachir Ahmed Nabil, Michalak Tomasz, Srivastava Gautam   +4 more
doaj   +1 more source

Assessment of Artificial Intelligence and Remote Sensing-Based groundwater storage management workflow

EQA
Groundwater is a vital freshwater reserve that is increasingly threatened by climate change and mounting anthropogenic pressure on global water resources.
Azeddine Elhassouny
doaj   +1 more source

Applications of Explainable Artificial Intelligence in Diagnosis and Surgery

Diagnostics, 2022
In recent years, artificial intelligence (AI) has shown great promise in medicine. However, explainability issues make AI applications in clinical usages difficult.
Yiming Zhang, Ying Weng, Jonathan Lund
doaj   +1 more source