Results 91 to 100 of about 17,459,905 (291)

Inhibition of cyclin‐dependent kinases 12/13 using CT7439 as a treatment for colorectal cancer with CDK12 upregulation

Molecular Oncology, EarlyView.
The proposed mechanism of action for the CDK12/13 inhibitor and cyclin K degrader, CT7439. CDK12/13 inhibition interrupts transcription elongation, leading to increased DNA damage that results in cell death. This agent is a potentially novel treatment option for patients with colorectal cancer. Created in BioRender. Cyclin‐dependent kinase (CDK) 12 and
Wylie K. Watlington, Divya L. Dayanidhi, Mohammad Zokaasadi, John B. Mantyh, Pelumi D. Olawuni, Gabrielle Rupprecht, Jeremy M. Force, Shannon McCall, Ashwani K. Bahl, David S. Hsu, Jason A. Somarelli   +10 more
wiley   +1 more source

A comparative study on medical image segmentation methods [PDF]

Applied Medical Informatics, 2014
Image segmentation plays an important role in medical images. It has been a relevant research area in computer vision and image analysis. Many segmentation algorithms have been proposed for medical images.
Praylin Selva Blessy SELVARAJ ASSLEY, Helen Sulochana CHELLAKKON   +1 more
doaj   +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

An Efficient Rapid Region Growing Algorithm for Medical Image Segmentation

, 2023
Medical imaging is an important diagnostic tool, so that medical personnel can more easily understand the patient's condition. Therefore, this study will combine medical knowledge and computer science to detect and capture the various features.
Chen*, Chii-Jen
core   +1 more source

Medical Image Segmentation

International Research Journal on Advanced Engineering Hub (IRJAEH)
Medical image segmentation is a critical component in the development of computer-aided diagnosis and treatment planning systems. This paper provides a comprehensive survey of recent advances in segmentation techniques applied to various imaging modalities, including Magnetic Resonance Imaging (MRI).
null Arpit Mohankar, null Aishwarya Nagpure, null Sania Shaikh, null Khushi Singh, null Firdous Jahan Shaikh   +4 more
openaire   +2 more sources

Advances in Medical Image Segmentation: A Comprehensive Review of Traditional, Deep Learning and Hybrid Approaches

Bioengineering
Medical image segmentation plays a critical role in accurate diagnosis and treatment planning, enabling precise analysis across a wide range of clinical tasks. This review begins by offering a comprehensive overview of traditional segmentation techniques,
Yan Xu, Rixiang Quan, Weiting Xu, Yi Huang, Xiaolong Chen, Fengyuan Liu   +5 more
doaj   +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

Shortcut Learning in Medical Image Segmentation

Shortcut learning is a phenomenon where machine learning models prioritize learning simple, potentially misleading cues from data that do not generalize well beyond the training set. While existing research primarily investigates this in the realm of image classification, this study extends the exploration of shortcut learning into medical image ...
Manxi Lin, Nina Weng, Kamil Wojciech Mikolaj, Zahra Bashir, Morten Bo Søndergaard Svendsen, Martin Grønnebæk Tolsgaard, Anders Nymark Christensen, Aasa Feragen   +7 more
openaire   +6 more sources

Intrapatient tumour heterogeneity and clonal evolution in an autopsy study of metastatic salivary gland cancer

Molecular Oncology, EarlyView.
Tumour heterogeneity and clonal evolution of metastatic salivary gland cancer were evaluated in two patients with adenoid carcinoma and one patient with myoepithelial carcinoma. Radiology‐guided autopsy enabled multi‐region sampling (total samples n = 149), followed by whole‐genome sequencing and phylogenetic reconstruction (17 tumour samples, 4–7 per ...
Gerben Lassche, Niels J. van Ruitenbeek, Charlotte Adang, Luke O'Gorman, Pui Yuen Lee, Willemijn M. Klein, Adriana C. H. van Engen‐van Grunsven, Jack A. Schalken, Sander Bervoets, Gerald W. Verhaegh, Carla M. L. van Herpen   +10 more
wiley   +1 more source

Profiling neoadjuvant therapy response in rectal cancer using meta‐analysis of publicly available transcriptomic RNA‐seq datasets

Molecular Oncology, EarlyView.
This study integrates publicly available transcriptomic datasets to identify molecular signatures associated with response to neoadjuvant chemoradiotherapy in locally advanced rectal cancer. By analyzing a combination of multiple cohorts with bioinformatics approaches, we reveal biological pathways and immune‐related features that may improve ...
Aleksandra Stanojevic, Rafael Stroggilos, Mladen Marinkovic, Ana Djuric, Suzana Stojanovic‐Rundic, Radmila Jankovic, Sergi Castellvi‐Bel, Remond J.A. Fijneman, Antonia Vlahou, Jerome Zoidakis, Milena Cavic   +10 more
wiley   +1 more source