Results 141 to 150 of about 2,787,379 (259)

Automated Alzheimer's disease detection using active learning model with reinforcement learning and scope loss function. [PDF]

Npj Ment Health Res
He Z, Govindarajan V, Yang J, Abdel-Salam M, Shaikh ZA, Por LY, Alizadehsani R, Tan RS, Rajendra Acharya U.   +8 more
europepmc   +1 more source

In vitro and in silico modelling of ROS1‐positive non‐small cell lung cancer reveals fusion‐dependent tyrosine kinase inhibitor responses

Molecular Oncology, EarlyView.
Drug resistance limits treatment success in a subset of lung cancers driven by ROS1 gene alterations. Using patient‐derived cells and computer simulations, we studied three key mutations and how they affect five targeted drugs. The mutations reduced drug effectiveness in different ways by altering protein structure and behavior.
Farhan Ul Haq, Marc Terrones, Felicia Rodrigues Fortes, Anne Schepers, Alessia Denis, Christophe Deben, Ken Op de Beeck, Guy Van Camp, Geert Vandeweyer   +8 more
wiley   +1 more source

A context aware multiclass loss function for semantic segmentation with a focus on intricate areas and class imbalances. [PDF]

Sci Rep
Ghanaei Z, Rouhani M.
europepmc   +1 more source

ZW4864‐mediated inhibition of the β‐catenin/BCL9/BCL9L complex reveals therapeutic potential in bladder cancer

Molecular Oncology, EarlyView.
BCL9 and BCL9L drive bladder cancer progression by enhancing β‐catenin signaling, promoting proliferation, migration, invasion, and organoid growth. Genetic depletion of BCL9(L) suppresses malignant phenotypes, while pharmacological disruption of the β‐catenin/BCL9(L) complex with ZW4864 inhibits canonical Wnt signaling and tumor‐associated cellular ...
Roland Kotolloshi, Mandy Berndt‐Paetz, Eileen Lerner, Gregoire Najjar, Anca Azoitei, Krishna Pal Singh, Shailendra Kumar Gupta, Olaf Wolkenhauer, Cagatay Günes, Otmar Huber, Marc‐Oliver Grimm, Daniel Steinbach   +11 more
wiley   +1 more source

Robust propensity score estimation via loss function calibration. [PDF]

Stat Methods Med Res
Shang Y, Chiu YH, Kong L.
europepmc   +1 more source

Loss Functions

, 2013
openaire   +2 more sources

Circulating microRNA signatures of cachexia and cancer in Canis familiaris as a comparative oncology model for human disease

Molecular Oncology, EarlyView.
Circulating microRNAs as biomarkers of cachexia and sex‐specific cancer in senior dogs. In 25 client‐owned dogs, four circulating miRNAs (miR‐15a, miR‐15b, miR‐16, miR‐140) were downregulated in cachexia, with miR‐16 the strongest individual biomarker (AUC = 0.899).
Soon‐Seok Park, Kyongman An, Gyeonghwa Kim, Soo‐Nyun Choi, Hong‐Ki Lee, Keun Hur, Kyu‐Shik Jeong   +6 more
wiley   +1 more source

A Method for Constructing a Loss Function for Multi-Scale Object Detection Networks. [PDF]

Sensors (Basel)
Wang D, Zhu H, Zhao Y, Shi J.
europepmc   +1 more source

The establishment and application of quality gain-loss function when the loss of primary and cubic term is not ignored and the compensation quantity is constant. [PDF]

PLoS One, 2023
Wang B, Li X, Shi J, Li Q, Nie X.
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