Results 151 to 160 of about 6,924,037 (250)

A novel rumor detection with multi-objective loss functions in online social networks. [PDF]

Expert Syst Appl, 2023
Wan P, Wang X, Pang G, Wang L, Min G.
europepmc   +1 more source

Cancer‐associated mutations in endometriosis reframe a benign disease through molecular oncology

Molecular Oncology, EarlyView.
This review aims to comprehensively analyse cancer‐associated somatic mutations (CAMs) present in endometriotic lesions, emphasizing their biological roles, spatial distribution and implications for translational applications in medicine. By contextualizing a benign state within a genomic framework, this analysis seeks to establish its value as a ...
Clarissa Mujacic, Maria Concetta Vitale, Rita Siino, Emilia Di Giovanni, Carla Ferrante Bannera, Enrico Di Marco, Andrea Gottardo, Tancredi Didier Bazan Russo, Nadia Barraco, Alessandro Perez, Valerio Gristina, Antonio Galvano, Giuseppe Badalamenti, Antonio Russo, Viviana Bazan, Lorena Incorvaia   +15 more
wiley   +1 more source

Bayesian Robustness with Quantile Loss

, 2007
Bayes decision problems require subjective elicitation of the inputs: beliefs and preferences. Sometimes, elicitation methods may not perfectly represent the Decision Maker's judgements.
J. Hernández, A. Suárez, J. Martín, Functions Arias Hern   +3 more
core  

Novel loss functions for ensemble-based medical image classification. [PDF]

PLoS One, 2021
Rajaraman S, Zamzmi G, Antani SK.
europepmc   +1 more source

Preoperative circulating tumor cells integrated with imaging analysis for prognostic evaluation in head and neck squamous cell carcinoma

Molecular Oncology, EarlyView.
Detecting circulating tumor cells (CTCs) in blood before surgery may help predict outcomes in patients with head and neck squamous cell carcinoma (HNSCC). Here, we show when combined with tumor size and lymph node involvement from routine imaging, CTC status identifies high‐risk patients with poorer survival—offering a simple, minimally invasive tool ...
Susanne Flach, Gizem Abaci, Tom Huberty, Axel Lechner, Lukas Käsmann, Jens Ricke, Sophia Stöcklein, Martin Canis, Philipp Baumeister, Marianna Alunni‐Fabbroni   +9 more
wiley   +1 more source

Deep learning-based dose prediction in proton beam therapy for hepatocellular carcinoma: comparison of network architectures and loss functions. [PDF]

J Radiat Res
Ogawa S, Kadoya N, Kato T, Kato R, Tozuka R, Narita Y, Oyama S, Murakami M, Jingu K.   +8 more
europepmc   +1 more source

Low-Light Image Enhancement Using Hybrid Deep-Learning and Mixed-Norm Loss Functions. [PDF]

Sensors (Basel), 2022
Oh J, Hong MC.
europepmc   +1 more source

Epigenetic silencing of the liver‐specific lncRNA LUNAR promotes liver cancer progression via NOTCH activation

Molecular Oncology, EarlyView.
LUNAR is a liver‐specific long noncoding RNA (lncRNA) that is highly expressed in normal liver but becomes epigenetically silenced in hepatocellular carcinoma through promoter hypermethylation. Loss of LUNAR is associated with NOTCH activation, epithelial–mesenchymal transition, and metastasis, whereas restoring LUNAR restrains metastatic progression ...
Se Ha Jang, Hyung Seok Kim, Geum Ok Baek, Moon Gyeong Yoon, Su In Lee, Jee‐Yeong Jeong, Ji Eun Han, Soon Sun Kim, Jae Youn Cheong, Jung Woo Eun   +9 more
wiley   +1 more source

Methods for Combining Conflicting Loss Functions

METHODS FOR COMBINING CONFLICTING LOSS FUNCTIONS Methods for Combining Conflicting Loss Functions / Deckers, Niklas (Rights reserved) (-
Deckers, Niklas
core  

Enhancing cross-modal retrieval via label graph optimization and hybrid loss functions. [PDF]

Sci Rep
Wang L, Wang C, Peng S.
europepmc   +1 more source