Results 171 to 180 of about 12,143,956 (343)

A Statistical Learning-Based Clustering Model With Features Selection to Identify Dyslexia in School-Aged Children. [PDF]

Dyslexia
Maiella M, Benedetti M, Alaimo Di Loro P, Maruotti A.   +3 more
europepmc   +1 more source

Detecting homologous recombination deficiency for breast cancer through integrative analysis of genomic data

Molecular Oncology, EarlyView.
This study develops a semi‐supervised classifier integrating multi‐genomic data (1404 training/5893 validation samples) to improve homologous recombination deficiency (HRD) detection in breast cancer. Our method demonstrates prognostic value and predicts chemotherapy/PARP inhibitor sensitivity in HRD+ tumours.
Rong Zhu, Katherine Eason, Suet‐Feung Chin, Paul A. W. Edwards, Raquel Manzano Garcia, Richard Moulange, Jia Wern Pan, Soo Hwang Teo, Sach Mukherjee, Maurizio Callari, Carlos Caldas, Stephen‐John Sammut, Oscar M. Rueda   +12 more
wiley   +1 more source

Multidisciplinary Delphi study validated variables for calculating cost of medication errors in the Sri Lankan context. [PDF]

BMJ Open Qual
Ranasinghe S, Navodya D, Nadeshkumar A, Senadheera S, Samaranayake N.   +4 more
europepmc   +1 more source

Evaluation of KRAS and NRAS mutations in metastatic colorectal cancer: an 8‐year study of 10 754 patients in Turkey

Molecular Oncology, EarlyView.
This nationwide study evaluated KRAS and NRAS mutations in 10 754 Turkish patients with metastatic colorectal cancer. The results revealed a mutation frequency of 51.1%, with 46.6% having KRAS mutations, 4.5% having NRAS mutations, and 48.5% being wild‐type for both.
Gozde Kavgaci, Izzet Akiva, Yavuz Hakan Ozon, Hakan Berkil, Huseyin Karadayi, Omer Dizdar, Suayib Yalcin   +6 more
wiley   +1 more source

Sur les fonctions de deux variables réelles [PDF]

, 1896
Émile Borel
openalex   +1 more source

Exploration of Likert scale in terms of continuous variable with parametric statistical methods. [PDF]

BMC Med Res Methodol
Huh I, Gim J.
europepmc   +1 more source

Data‐driven discovery of gene expression markers distinguishing pediatric acute lymphoblastic leukemia subtypes

Molecular Oncology, EarlyView.
This study investigates gene expression differences between two major pediatric acute lymphoblastic leukemia (ALL) subtypes, B‐cell precursor ALL, and T‐cell ALL, using a data‐driven approach consisting of biostatistics and machine learning methods. Following analysis of a discovery dataset, we find a set of 14 expression markers differentiating the ...
Mona Nourbakhsh, Nikola Tom, Anna Schrøder Lassen, Helene Brasch Lind Petersen, Ulrik Kristoffer Stoltze, Karin Wadt, Kjeld Schmiegelow, Matteo Tiberti, Elena Papaleo   +8 more
wiley   +1 more source

A machine learning model guided by physical principles for biofilter performance prediction. [PDF]

Sci Rep
Uzma, Cholet F, Quinn D, Smith CJ, You S, Sloan WT.   +5 more
europepmc   +1 more source

MicroRNA 196a contributes to the aggressiveness of esophageal adenocarcinoma through the MYC/TERT/NFκB axis

Molecular Oncology, EarlyView.
mir‐196a promotes Esophagus Adenocarcinoma aggressiveness. On one hand, mir‐196a targets the valosin‐containing protein (VCP) mRNA, causing the accumulation of c‐MYC protein that leads to high amounts of TERT. On the other hand, mir‐196a targets the inhibitor of NFκB (NFKBIA).
Jesús García‐Castillo, Carlos M. Martínez‐Cáceres, Manuel Bernabé‐García, Vicente Munitiz, David Ruiz de Angulo, Pascual Parrilla, Ángeles Ortiz, Luisa F. Martínez de Haro, María L. Cayuela   +8 more
wiley   +1 more source

Dataset-Learning Duality and Emergent Criticality. [PDF]

Entropy (Basel)
Kukleva E, Vanchurin V.
europepmc   +1 more source