Results 51 to 60 of about 1,248,762 (236)

Cycles in adversarial regularized learning [PDF]

, 2017
Regularized learning is a fundamental technique in online optimization, machine learning and many other fields of computer science. A natural question that arises in these settings is how regularized learning algorithms behave when faced against each ...
Mertikopoulos, Panayotis, Papadimitriou, Christos, Piliouras, Georgios   +2 more
core   +1 more source

Fuzzy Machine Learning: A Comprehensive Framework and Systematic Review

IEEE transactions on fuzzy systems
Machine learning draws its power from various disciplines, including computer science, cognitive science, and statistics. Although machine learning has achieved great advancements in both theory and practice, its methods have some limitations when ...
Jie Lu, Guangzhi Ma, Guangquan Zhang
semanticscholar   +1 more source

Hospital Readmission After Traumatic Brain Injury Hospitalization in Community‐Dwelling Older Adults

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To examine the risk of hospital readmission after an index hospitalization for TBI in older adults. Methods Using data from the Atherosclerosis Risk in Communities (ARIC) study, we used propensity score matching of individuals with an index TBI‐related hospitalization to individuals with (1) non‐TBI hospitalizations (primary analysis)
Rachel Thomas, Connor A. Law, Joan A. Casey, Thomas Mosley, Rebecca F. Gottesman, Ramon Diaz‐Arrastia, Holly Elser, Andrea L. C. Schneider   +7 more
wiley   +1 more source

Pedagogical Possibilities for the N-Puzzle Problem

, 2006
In this paper we present work on a project funded by the National Science Foundation with a goal of unifying the Artificial Intelligence (AI) course around the theme of machine learning.
Markov, Zdravko, Neller, Todd W., Russell, Ingrid, Zlatareva, Neli   +3 more
core   +1 more source

Bias in Machine Learning: A Literature Review

Applied Sciences
Bias could be defined as the tendency to be in favor or against a person or a group, thus promoting unfairness. In computer science, bias is called algorithmic or artificial intelligence (i.e., AI) and can be described as the tendency to showcase ...
Konstantinos Mavrogiorgos, Athanasios Kiourtis, Argyro Mavrogiorgou, A. Menychtas, D. Kyriazis   +4 more
semanticscholar   +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

The Challenges of Machine Learning: A Critical Review

Electronics
The concept of learning has multiple interpretations, ranging from acquiring knowledge or skills to constructing meaning and social development. Machine Learning (ML) is considered a branch of Artificial Intelligence (AI) and develops algorithms that can
Enrico Barbierato, Alice Gatti
semanticscholar   +1 more source

Remote Monitoring in Myasthenia Gravis: Exploring Symptom Variability

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background Myasthenia gravis (MG) is a rare, autoimmune disorder characterized by fluctuating muscle weakness and potential life‐threatening crises. While continuous specialized care is essential, access barriers often delay timely interventions. To address this, we developed MyaLink, a telemedical platform for MG patients.
Maike Stein, Maximilian Mönch, Meret Herdick, Frauke Stascheit, Sarah Hoffmann, Hannah Preßler, Philipp Mergenthaler, Carla Dusemund, Paolo Doksani, Haoqi Sun, Pushpa Narayanaswami, Andreas Meisel, Lea Gerischer, Sophie Lehnerer   +13 more
wiley   +1 more source

How Much Information is in a Jet?

, 2017
Machine learning techniques are increasingly being applied toward data analyses at the Large Hadron Collider, especially with applications for discrimination of jets with different originating particles.
Datta, Kaustuv, Larkoski, Andrew
core   +1 more source

Development of a Prediction Model for Progression Risk in High‐Grade Gliomas Based on Habitat Radiomics and Pathomics

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To investigate the value of constructing models based on habitat radiomics and pathomics for predicting the risk of progression in high‐grade gliomas. Methods This study conducted a retrospective analysis of preoperative magnetic resonance (MR) images and pathological sections from 72 patients diagnosed with high‐grade gliomas (52 ...
Yuchen Zhu, Yuxi Gong, Weilin Xu, Xingjian Sun, Gefei Jiang, Lei Qiu, Kexin Shi, Mengxing Wu, Yinjiao Fei, Jinling Yuan, Jinyan Luo, Yurong Li, Yuandong Cao, Minhong Pan, Shu Zhou   +14 more
wiley   +1 more source