Results 151 to 160 of about 2,787,379 (259)

Enhanced Pelvic CT Segmentation via Deep Learning: A Study on Loss Function Effects. [PDF]

J Imaging Inform Med
Ghaedi E, Asadi A, Hosseini SA, Arabi H.
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

Auto-segmentation and dose accuracy evaluation of synthetic computed tomography generated from pelvis cone-beam computed tomography images using a cycle-generative adversarial network with a novel loss function. [PDF]

Phys Imaging Radiat Oncol
Anbumani S, Keeler A, Xu J, Thill D, O'Connell N, Paulson E, Shukla ME, Omari EA.   +7 more
europepmc   +1 more source

Raman spectroscopy-based prediction of ofloxacin concentration in solution using a novel loss function and an improved GA-CNN model. [PDF]

BMC Bioinformatics, 2023
Ma C, Shi Y, Huang Y, Dai G.
europepmc   +1 more source

Translating whole‐genome doubling into precision medicine in cancer

Molecular Oncology, EarlyView.
Whole‐genome doubling creates a WGD‐positive tumor state characterized by persistent chromosomal instability, karyotypic diversification, and cellular stress. These same biological pressures drive aggressive tumor evolution while exposing therapeutic vulnerabilities, providing a rationale for WGD‐informed precision medicine. Whole‐genome doubling (WGD)
Sejung Lee, Junghyeok Lim, Jinhyuk Bhin
wiley   +1 more source

Optimized UNet framework with a joint loss function for underwater image enhancement. [PDF]

Sci Rep
Wang X, Luo Z, Huang W, Zhang Y, Hu R.
europepmc   +1 more source

Single‐cell DNA methylation profiling: Technologies, computation, and applications in precision oncology

Molecular Oncology, EarlyView.
Single‐cell DNA methylation (scDNAme) profiling maps epimutational clonal evolution, revealing mechanisms of malignancy and therapeutic resistance across diverse cancer types. By providing a high‐resolution landscape of intratumoral heterogeneity, these technologies empower precise patient stratification, guide the development of enhanced ...
Ik Soo Kim
wiley   +1 more source

Dual-level weighted cross-entropy loss function and multi-object region segmentation network evaluation for dynamic knee joint X-ray radiography based on a novel scoring criterion. [PDF]

Front Med (Lausanne)
Wang S, Wu T, Huang W, Du J, Chen Z, Xiao Z, Gao Q, Liu Y, Chen Y, Guo P, Zeng N, Liao J, Yang Y, Zheng J, Chen H, Liu Y, Lv F.   +16 more
europepmc   +1 more source

Targeting transcription factors associated with hemoglobinopathies: Lessons from successful interventions and implications for cancer

Molecular Oncology, EarlyView.
This review summarizes the transcription factors, repressive chromatin‐modifying complexes, and epigenetic mechanisms that control fetal hemoglobin repression. Notably, many regulators of γ‐globin silencing also function in transcriptional and epigenetic networks that drive cancer, highlighting opportunities to translate advances in hemoglobinopathy ...
Meigen Yu, Puspa Das, Xing Zhang, Xiaodong Cheng   +3 more
wiley   +1 more source

CrackNet: A Hybrid Model for Crack Segmentation with Dynamic Loss Function. [PDF]

Sensors (Basel)
Fan Y, Hu Z, Li Q, Sun Y, Chen J, Zhou Q.   +5 more
europepmc   +1 more source