Results 91 to 100 of about 1,981,486 (333)

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

Artificial Intelligence and Spirituality.

International Journal of Interactive Multimedia and Artificial Intelligence, 2021
Drawing from a conceptual review of the terms ‘mind’, ‘intelligence’, ‘spirit’, ‘spirituality’, ‘spiritual intelligence’ and their possible interrelations, an approach to the concept ‘human nature’ is made in relation to transhumanism and post-humanism.
openaire   +4 more sources

Enhanced prediction of hemolytic activity in antimicrobial peptides using deep learning-based sequence analysis

BMC Bioinformatics
Antimicrobial peptides (AMPs) are a promising class of antimicrobial drugs due to their broad-spectrum activity against microorganisms. However, their clinical application is limited by their potential to cause hemolysis, the destruction of red blood ...
Ibrahim Abdelbaky, Mohamed Elhakeem, Hilal Tayara, Elsayed Badr, Mustafa Abdul Salam   +4 more
doaj   +1 more source

Nature-Inspired Intelligent Computing: A Comprehensive Survey

Research
Nature, with its numerous surprising rules, serves as a rich source of creativity for the development of artificial intelligence, inspiring researchers to create several nature-inspired intelligent computing paradigms based on natural mechanisms.
Licheng Jiao, Jiaxuan Zhao, Chao Wang, Xu Liu, Fang Liu, Lingling Li, Ronghua Shang, Yangyang Li, Wenping Ma, Shuyuan Yang   +9 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

A Formal Measure of Machine Intelligence

, 2006
A fundamental problem in artificial intelligence is that nobody really knows what intelligence is. The problem is especially acute when we need to consider artificial systems which are significantly different to humans.
Hutter, Marcus, Legg, Shane
core   +3 more sources

The Use of Artificial Intelligence to Promote Autonomous Pronunciation Learning: Segmental and Suprasegmental Features Perspective [PDF]

, 2023
Senowarsito Senowarsito, Sukma Nur Ardini   +1 more
openalex   +1 more source

The Tong Test: Evaluating Artificial General Intelligence Through Dynamic Embodied Physical and Social Interactions

Engineering
The release of the generative pre-trained transformer (GPT) series has brought artificial general intelligence (AGI) to the forefront of the artificial intelligence (AI) field once again.
Yujia Peng, Jiaheng Han, Zhenliang Zhang, Lifeng Fan, Tengyu Liu, Siyuan Qi, Xue Feng, Yuxi Ma, Yizhou Wang, Song-Chun Zhu   +9 more
doaj   +1 more source

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

Enhancing anomaly detection in IoT-driven factories using Logistic Boosting, Random Forest, and SVM: A comparative machine learning approach

Scientific Reports
Three machine learning algorithms—Logistic Boosting, Random Forest, and Support Vector Machines (SVM)—were evaluated for anomaly detection in IoT-driven industrial environments.
Mohammed Aly, Mohamed H. Behiry
doaj   +1 more source