Results 81 to 90 of about 1,902,998 (334)

Artificial Intelligence dalam Penanganan Komplain Pelanggan pada Industri Coating [PDF]

, 2015
Banyak Perusahaan saat ini memikirkan cara untuk memelihara hubungan baik mereka dengan para pelanggannya. Bukan hanya masalah loyalitas, meraih lebih banyak pelanggan juga menjadi tantangan besar.
Handayani, I. (Indri), Listiyoko, L. (Langgeng), N, L. N. (Listina)   +2 more
core  

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

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

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

Self-Building Artificial Intelligence and Machine Learning to Empower Big Data Analytics in Smart Cities [PDF]

, 2020
Damminda Alahakoon, Rashmika Nawaratne, Yan Xu, Daswin De Silva, Uthayasankar Sivarajah, Bhumika Gupta   +5 more
openalex   +1 more source

Artificial intelligence in space

, 2020
In the next coming years, space activities are expected to undergo a radical transformation with the emergence of new satellite systems or new services which will incorporate the contributions of artificial intelligence and machine learning defined as covering a wide range of innovations from autonomous objects with their own decision-making power to ...
Long, George Anthony, Santos, Cristiana, Rapp, Lucien, Markovich, Réka, van der Torre, Leon   +4 more
openaire   +3 more sources

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

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

AlphaFold, Artificial Intelligence (AI), and Allostery

, 2022
Ruth Nussinov, Mingzhen Zhang, Yonglan Liu, Hyunbum Jang   +3 more
openalex   +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