Results 41 to 50 of about 40,856 (264)
Hepatic Glycogen Storage Diseases in Brazil: A Multicenter Study
American Journal of Medical Genetics Part A, EarlyView.ABSTRACT To describe clinical and laboratory characteristics, emphasizing the evolution of patients with hepatic glycogen storage diseases (GSDs) followed in Brazilian reference centers. Multicenter, retrospective study involving 13 centers, using RedCap platform. 132 patients were included: 63 (47.8%) GSD type I (56 Ia, 7 Ib), 13 (9.8%) with type III (
Mariana Pena Costa +23 more
wiley +1 more source
Misclassification analysis for the class imbalance problem [PDF]
, 2010 In classification, the class imbalance issue normally causes the learning algorithm to be dominated by the majority classes and the features of the minority classes are sometimes ignored.
Fung, C.C. +3 more
core +1 more source
Early Identification of Violent Criminal Gang Members
, 2015 Gang violence is a major problem in the United States accounting for a large fraction of homicides and other violent crime. In this paper, we study the problem of early identification of violent gang members.
Bertetto J. +6 more
core +1 more source
American Journal of Medical Genetics Part B: Neuropsychiatric Genetics, EarlyView.ABSTRACT In epidemiological studies, obsessive‐compulsive disorder (OCD) is robustly associated with increased risk of cardiometabolic disorders, including cardiovascular diseases, type 2 diabetes, and obesity. However, the mechanisms behind these associations are unclear. We conducted genetic correlation analyses to explore shared genetic etiology and
Robyn E. Wootton +217 more
wiley +1 more source
PREDICTION OF HAJJ PILGRIMS' HEALTH RISK USING K-NN, DECISION TREE, CROSS VALIDATION, AND SMOTE
Techno Nusa Mandiri: Journal of Computing and Information TechnologyThe background of this study is predicting the health risk levels of hajj pilgrims, which is a significant challenge in improving healthcare services during the pilgrimage.
Widi Astuti, Fajar Sarasati
doaj +1 more source
SMOTE: Synthetic Minority Over-sampling Technique
Journal of Artificial Intelligence Research, 2002 An approach to the construction of classifiers from imbalanced datasets is described. A dataset is imbalanced if the classification categories are not approximately equally represented. Often real-world data sets are predominately composed of ``normal'' examples with only a small percentage of ``abnormal'' or ``interesting'' examples. It
Chawla, N. V. +3 more
openaire +4 more sources
Chronological Diagnostic Algorithm Predicting Neuropathology in Parkinsonism
Annals of Neurology, EarlyView.Objective Pre‐mortem diagnosis of parkinsonism is often challenging due to atypical presentations, overlapping syndromes, and co‐pathologies. This study aimed to develop a machine learning‐based algorithm predicting neuropathology in parkinsonism using chronological clinical presentations, which has previously been underexplored.
Daisuke Ono +5 more
wiley +1 more source
Skeletal pathologies in extant crocodilians as a window into the paleopathology of fossil archosaurs
The Anatomical Record, EarlyView.Abstract Crocodilians, together with birds, are the only extant relatives to many extinct archosaur groups, making them highly important for interpreting paleopathological conditions in a phylogenetic disease bracketing model. Despite this, comprehensive data on osteopathologies in crocodilians remain scarce.
Alexis Cornille +6 more
wiley +1 more source
Sentiment Analysis Mobile JKN Reviews Using SMOTE Based LSTM
IJCCS (Indonesian Journal of Computing and Cybernetics Systems)The JKN Mobile application plays an important role in providing easy and fast access to health services for JKN-KIS users. However, user reviews indicate dissatisfaction with several aspects of the application, such as login issues and OTP codes, which ...
Ghufron Tamami +2 more
doaj +1 more source
Comparison of Sampling Techniques for Imbalanced Data Classification
วารสารวิทยาการสารสนเทศและเทคโนโลยีประยุกต์, 2018 Imbalanced data is a problem in the machine learning process for data classification, which results in low classification efficiency. It has also been found that random sampling techniques are used in several ways for solving low performance problems due
Karn Nasritha +2 more
doaj +1 more source