Results 41 to 50 of about 76,023 (254)

Frailty Exacerbates Disability in Progressive Multiple Sclerosis

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background To evaluate frailty in severe progressive multiple sclerosis (PMS) and to investigate the underlying mechanisms. Methods This prospective, cross‐sectional, multicenter study enrolled a late severe PMS group requiring skilled nursing (n = 53) and an age, sex, and disease duration‐matched control PMS group (n = 53).
Taylor R. Wicks, Anna Wolska, Diala Ghazal, Dejan Jakimovski, Bianca Weinstock‐Guttman, Alexander Burnham, Niels Bergsland, Michael G. Dwyer, Alan T. Remaley, Robert Zivadinov, Murali Ramanathan   +10 more
wiley   +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

Ontologies for Smart Agriculture: A Path Toward Explainable AI—A Systematic Literature Review

IEEE Access
Smart agriculture has grown significantly over the last few years, particularly with the integration of advanced technologies (e.g., the Internet of Things, robots, artificial intelligence, etc.), leading to the development of intelligent agricultural ...
Rima Grati, Najla Fattouch, Khouloud Boukadi   +2 more
doaj   +1 more source

Prediction of Myasthenia Gravis Worsening: A Machine Learning Algorithm Using Wearables and Patient‐Reported Measures

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background Myasthenia gravis (MG) is a rare disorder characterized by fluctuating muscle weakness with potential life‐threatening crises. Timely interventions may be delayed by limited access to care and fragmented documentation. Our objective was to develop predictive algorithms for MG deterioration using multimodal telemedicine data ...
Maike Stein, Haoqi Sun, Sophie Lehnerer, Lea Gerischer, Maximilian Mönch, Christian Meisel, Andreas Meisel, Pushpa Narayanaswami   +7 more
wiley   +1 more source

Explainable Artificial Intelligence and Legal Ethos: Developing Key Performance Indicators for ‘G20 Giants’

Journal of Digital Technologies and Law
Objective: to study the “right to explanation” in the context of the PEEC doctrine (public interest, environmental sustainability, economic development, criminal justice) in order to develop key performance indicators reflecting the socio-cultural ...
N. Bhatt, J. N. Bhatt
doaj   +1 more source

Explainable artificial intelligence: A survey

2018 41st International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO), 2018
In the last decade, with availability of large datasets and more computing power, machine learning systems have achieved (super)human performance in a wide variety of tasks. Examples of this rapid development can be seen in image recognition, speech analysis, strategic game planning and many more. The problem with many state-of-the-art models is a lack
Došilović, Filip Karlo, Brčić, Mario, Hlupić, Nikica   +2 more
openaire   +2 more sources

Predicting Epileptogenic Tubers in Patients With Tuberous Sclerosis Complex Using a Fusion Model Integrating Lesion Network Mapping and Machine Learning

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Accurate localization of epileptogenic tubers (ETs) in patients with tuberous sclerosis complex (TSC) is essential but challenging, as these tubers lack distinct pathological or genetic markers to differentiate them from other cortical tubers.
Tinghong Liu, Qi Wang, Suhui Kuang, Dezhi Cao, Ping Ding, Shaohui Zhang, Haihua Wei, Zhirong Wei, Jinshan Xu, Xinyu Huang, Bing Liu, Shuli Liang   +11 more
wiley   +1 more source

Toward Accountable and Explainable Artificial Intelligence Part One: Theory and Examples

IEEE Access, 2022
Like other Artificial Intelligence (AI) systems, Machine Learning (ML) applications cannot explain decisions, are marred with training-caused biases, and suffer from algorithmic limitations.
Masood M. Khan, Jordan Vice
doaj   +1 more source

Explainable Artificial Intelligence

, 2022
Every decade technology makes revolutionary shifts that become the new platforms on which application technology is built. Artificial intelligence AI is no different. AI has moved from 1st Generation shallow learning and handcrafted features to 2nd Generation deep learning, which has been effective at learning patterns.
Averchin, A., Averkin, A.
openaire   +1 more source

Applying an Ethical Lens to the Treatment of People With Multiple Sclerosis

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT The practice of neurology requires an understanding of clinical ethics for decision‐making. In multiple sclerosis (MS) care, there are a wide range of ethical considerations that may arise. These involve shared decision‐making around selection of a disease‐modifying therapy (DMT), risks and benefits of well‐studied medications in comparison to
Methma Udawatta, Farrah J. Mateen
wiley   +1 more source