Results 91 to 100 of about 4,042,759 (279)

Human centred explainable AI decision-making in healthcare

Journal of Responsible Technology
Human-centred AI (HCAI11 HCAI – Human-centred artificial intelligence) implies building AI systems in a manner that comprehends human aims, needs, and expectations by assisting, interacting, and collaborating with humans.
Catharina M. van Leersum, Clara Maathuis
doaj   +1 more source

Revolutionizing breast ultrasound diagnostics with EfficientNet-B7 and Explainable AI

BMC Medical Imaging
Breast cancer is a leading cause of mortality among women globally, necessitating precise classification of breast ultrasound images for early diagnosis and treatment.
M. Latha, P. S. Kumar, R. R. Chandrika, T. Mahesh, V. V. Kumar, Suresh Guluwadi   +5 more
semanticscholar   +1 more source

Fibrinogen Changes Before and After Intravenous Thrombolysis as Predictors of Cerebral Injury and Clinical Outcomes in Acute Ischemic Stroke: A Multicenter Prospective Cohort Study

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Plasma fibrinogen is essential in thrombosis and fibrinolysis, yet its dynamic changes pre‐ and post‐intravenous thrombolysis (IVT) for predicting brain injury severity and prognosis in acute ischemic stroke (AIS) patients remain unclear.
Wenhai Zhai, Yang Qu, Reziya Abuduxukuer, Kejia Zhang, Peng Zhang, Xin Tang, Huaimei Zhang, Lijuan Wang, Lichong Yang, Shuangxu Tan, Zhimei Yuan, Ce Han, Lili He, Yuping Zheng, Fenglan Zhao, Lijie Guo, Ligang Jiang, Jinfeng Li, Yongfei Jiang, Xuexia Zou, Dan Xu, Han Xu, Xiaojia Wang, Yingbin Qi, Xuefeng Hu, Yu Zhang, Zhen‐Ni Guo, Hang Jin, on behalf of the Biomarkers of Brain Injury Investigator Study Group   +28 more
wiley   +1 more source

Explainable AI Frameworks: Navigating the Present Challenges and Unveiling Innovative Applications

Algorithms
This study delves into the realm of Explainable Artificial Intelligence (XAI) frameworks, aiming to empower researchers and practitioners with a deeper understanding of these tools. We establish a comprehensive knowledge base by classifying and analyzing
Neeraj Anand Sharma, Rishal Ravikesh Chand, Zain Buksh, A. B. M. Shawkat Ali, Ambreen Hanif, Amin Beheshti   +5 more
doaj   +1 more source

XAI-IoT: An Explainable AI Framework for Enhancing Anomaly Detection in IoT Systems

IEEE Access
The exponential growth of Internet of Things (IoT) systems inspires new research directions on developing artificial intelligence (AI) techniques for detecting anomalies in these IoT systems. One important goal in this context is to accurately detect and
Anna Namrita Gummadi, Jerry C. Napier, Mustafa Abdallah   +2 more
semanticscholar   +1 more source

Deep Learning–Assisted Differentiation of Four Peripheral Neuropathies Using Corneal Confocal Microscopy

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Peripheral neuropathies contribute to patient disability but may be diagnosed late or missed altogether due to late referral, limitation of current diagnostic methods and lack of specialized testing facilities. To address this clinical gap, we developed NeuropathAI, an interpretable deep learning–based multiclass classification ...
Chaima Ben Rabah, Ioannis N. Petropoulos, Mark Stettner, Maryam Ferdousi, Uazman Alam, Nathan Efron, Ahmed Serag, Rayaz A. Malik   +7 more
wiley   +1 more source

From local explanations to global understanding with explainable AI for trees

Nature Machine Intelligence, 2020
Scott M. Lundberg, G. Erion, Hugh Chen, A. DeGrave, J. Prutkin, B. Nair, R. Katz, J. Himmelfarb, N. Bansal, Su-In Lee   +9 more
semanticscholar   +1 more source

Association of Corticospinal Tract Asymmetry With Ambulatory Ability After Intracerebral Hemorrhage

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background Ambulatory ability after intracerebral hemorrhage (ICH) is important to patients. We tested whether asymmetry between ipsi‐ and contra‐lesional corticospinal tracts (CSTs) assessed by diffusion tensor imaging (DTI) is associated with post‐ICH ambulation.
Yasmin N. Aziz, Carl D. Langefeld, Mary E. Comeau, Miranda C. Marion, Tyler P. Behymer, Lee A. Gilkerson, Padmini Sekar, Weihong Yuan, Vivek Khandwala, Brady J. Williamson, Thomas Maloney, Achala Vagal, Pierce Boyne, Kari Dunning, Matthew L. Flaherty, Steven J. Kittner, Prachi Mehndiratta, Gunjan Y. Parikh, Michael L. James, David Roh, Fernando D. Testai, Farhaan S. Vahidy, James Thornton, Ranjit Bagga, Daniel Woo, Stacie L. Demel   +25 more
wiley   +1 more source

Analyzing and assessing explainable AI models for smart agriculture environments

Multimedia tools and applications
We analyze a case study in the field of smart agriculture exploiting Explainable AI (XAI) approach, a field of study that aims to provide interpretations and explanations to the behaviour of AI systems.
Andrea Cartolano, Alfredo Cuzzocrea, Giovanni Pilato   +2 more
semanticscholar   +1 more source

Effects of Biological Sex and Age on Cerebrospinal Fluid Markers—A Retrospective Observational Study

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Cerebrospinal fluid (CSF) analysis is a key diagnostic tool for neurological diseases. To date, only a few studies have investigated in larger cohorts the effect of age and biological sex on diagnostic markers extracted from CSF. Methods For this retrospective observational study, 4163 CSF findings (2012–2020) were evaluated.
Isabel‐Sophie Hafer, Simon Faissner, Ralf Gold, Aiden Haghikia   +3 more
wiley   +1 more source