Results 191 to 200 of about 93,524 (286)

Machine learning strategies for predicting pediatric suicidal behaviors in a Brazilian emergency setting. [PDF]

Front Artif Intell
Carvalho IF, Couto da Silva AP, Lacerda AM, Meira W, Bastos Bispo Ferreira D, Malloy Diniz L, Serpa ALO, Machado MCL, Romano-Silva MA, de Miranda DM, Pappa GL.   +10 more
europepmc   +1 more source

Chemical Shift Separated and Compensated Ultra‐Short Echo‐Time Imaging

Magnetic Resonance in Medicine, Volume 96, Issue 1, Page 121-133, July 2026.
ABSTRACT Purpose To develop a modified binomial excitation scheme for ultra‐short echo‐time (UTE) imaging that allows for the separation of water and fat signals and the correction of chemical shift artifacts. Methods Theoretical derivation and numerical Bloch simulations were performed for a modified water‐excitation binomial pulse scheme to calculate
Martin Krämer, Lumeng Cui, Jürgen R. Reichenbach, Stefan Sommer   +3 more
wiley   +1 more source

A pruned and parameter-efficient Xception framework for skin cancer classification. [PDF]

PLoS One
Kılıç Ş, Doğan Y.
europepmc   +1 more source

Childhood Material Hardship Linked to Adolescent Neurocognition: A Computational Modeling Approach

Developmental Science, Volume 29, Issue 4, July 2026.
ABSTRACT Childhood material hardship, including insecurity in housing, utilities, food, and medical care, is a critical factor influencing cognitive functioning and mental health outcomes. However, past research on material hardship is limited by cross‐sectional data and reliance on conventional behavioral measures of cognitive functioning that suffer ...
Yue Linda Zhang, Alexander S. Weigard, Felicia A. Hardi, Sunghyun H. Hong, Edward Huntley, Colter Mitchell, Luke W. Hyde, Christopher S. Monk   +7 more
wiley   +1 more source

Phasing tiny crystals

IUCrJ, 2014
Jianwei Miao, Jose A. Rodriguez
doaj   +1 more source

The power of machine learning models in predicting gestational diabetes mellitus. [PDF]

BMC Pregnancy Childbirth
Mehrnoush V, Haghighat A, Nami A, Rezaei N, Darsareh F, Montazeri F, Saffari M.   +6 more
europepmc   +1 more source

A Survey for Deep Reinforcement Learning Based Network Intrusion Detection

Applied AI Letters, Volume 7, Issue 2, June 2026.
This paper surveys deep reinforcement learning (DRL) for network intrusion detection, evaluating model efficiency, minority attack detection, and dataset imbalance. Findings show DRL achieves state‐of‐the‐art results on public datasets, sometimes surpassing traditional deep learning.
Wanrong Yang, Alberto Acuto, Yihang Zhou, Dominik Wojtczak   +3 more
wiley   +1 more source

An algorithmic system for arabic fake news detection using neural networks and transformer embeddings with class weighting. [PDF]

Sci Rep
Saad M, Abdelrazek S, Abdelmaksoud IR.
europepmc   +1 more source

Clinical, Genetic, and Pathologic Variability in Myelodysplastic Syndromes and Precursor Conditions Across Race, Ethnicity, and Sex

American Journal of Hematology, Volume 101, Issue 6, Page 1407-1420, June 2026.
ABSTRACT The epidemiology of myelodysplastic syndromes/neoplasms (MDS) is challenging to define due to inconsistent reporting, complex diagnostic procedures, and evolving diagnostic criteria. Using the National MDS Natural History Study—a prospective cohort with centrally adjudicated histopathology and genetic variant review—we characterized the ...
Nancy Gillis, Christelle Colin‐Leitzinger, Yi‐Han Tang, Michael Otterstatter, Seth Sherman, Ling Zhang, Lynn C. Moscinski, Mary Ellen Walker, Jeffrey S. Painter, Gregory A. Abel, Tareq Al Baghdadi, H. Joachim Deeg, James M. Foran, Steven D. Gore, Alexandra M. Harrington, Steven H. Kroft, Jane Jijun Liu, Wael Saber, Shamsuddin Virani, Rafael Bejar, R. Coleman Lindsley, Eric Padron, Matthew J. Walter, Rami Komrokji, Amy E. DeZern, Mikkael A. Sekeres   +25 more
wiley   +1 more source

Cardiorespiratory Markers of Type 2 Diabetes: Machine Learning-Based Analysis. [PDF]

JMIR Diabetes
Oliveira FMGSA, Cavalcanti SM, Khoo MCK.
europepmc   +1 more source