Results 221 to 230 of about 8,124,451 (335)

Enriched lung cancer classification approach using an optimized hybrid deep learning approach. [PDF]

Sci Rep
Naveenraj M, Vijayakumar P.
europepmc   +1 more source

Meta‐analysis fails to show any correlation between protein abundance and ubiquitination changes

FEBS Open Bio, EarlyView.
We analyzed over 50 published proteomics datasets to explore the relationship between protein levels and ubiquitination changes across multiple experimental conditions and biological systems. Although ubiquitination is often associated with protein degradation, our analysis shows that changes in ubiquitination do not globally correlate with changes in ...
Nerea Osinalde, Unai Alduntzin, Gorka Prieto, Ugo Mayor   +3 more
wiley   +1 more source

Integrating Anatomical Site Information Into Vision Transformer Models for Skin Cancer Classification. [PDF]

Ann Dermatol
Ha DL, Jeong S, Woo D, Cho J, Lee WJ.
europepmc   +1 more source

Applicability of mitotic figure counting by deep learning: a development and pan‐cancer validation study

FEBS Open Bio, EarlyView.
In this study, we developed a deep learning method for mitotic figure counting in H&E‐stained whole‐slide images and evaluated its prognostic impact in 13 external validation cohorts from seven different cancer types. Patients with more mitotic figures per mm2 had significantly worse patient outcome in all the studied cancer types except colorectal ...
Joakim Kalsnes, Maria X. Isaksen, Frida Julbø, Manohar Pradhan, Andreas Kleppe, Sepp De Raedt, Ole‐Johan Skrede, Turid Torheim, John Arne Nesheim, Hans Martin Mohn, Hanne A. Askautrud, Karolina Cyll, Wanja Kildal, Emma Rewcastle, Melinda Lillesand, Vebjørn Kvikstad, Emiel Janssen, Robert Jones, Odd Terje Brustugun, Bjørn Brennhovd, Erik Skaaheim Haug, Lill‐Tove Rasmussen Busund, Elin Richardsen, Sigve Andersen, Tom Dønnem, Kristina Lindemann, Gunnar Kristensen, Neil A. Shepherd, Marco Novelli, Knut Liestøl, David Kerr, Håvard E. Danielsen, Tarjei S. Hveem   +32 more
wiley   +1 more source

Dynamic-Attentive Pooling Networks: A Hybrid Lightweight Deep Model for Lung Cancer Classification. [PDF]

J Imaging
Ayivi W, Zhang X, Ativi WX, Sam F, Kouassi FAP.   +4 more
europepmc   +1 more source

Enhancing Oncological Care for India's Aging Population: Addressing the Complex Needs of Older Adults With Cancer

Aging and Cancer, EarlyView.
Aging‐associated physiological and molecular alterations pose significant challenges in cancer management among India's elderly. Limited geriatric oncology expertise, financial constraints, and inadequate specialized care exacerbate disparities. Strategic expansion of insurance coverage, integration of palliative care, and infrastructural advancements ...
Nihanthy D. Sreenath, Mathigatta Shivarudraiah S, Rajath Govind, Kaushik M R   +3 more
wiley   +1 more source

DSSCC net enhanced skin cancer classification using SMOTE Tomek and optimized convolutional neural network. [PDF]

Sci Rep
Javaid MA, Shahzad MS, Shehzad HMF, Razzaq S, Ali S, Shah D, Tahir M.   +6 more
europepmc   +1 more source

Natural Products as Geroprotective Modulators in Diabetic Nephropathy: A Mechanistic Framework Integrating Aging Hallmarks and the AMPK–SIRT1–Nrf2 Axis

Aging and Cancer, EarlyView.
Natural products target the aging kidney in diabetic nephropathy by restoring the AMPK–SIRT1–Nrf2 axis, reducing oxidative stress, inflammation, fibrosis, and cellular senescence while enhancing mitochondrial biogenesis and antioxidant defenses.
Sherif Hamidu, Latif Adams, Eunice Ampem‐Danso, Justice Kumi, Abigail Aning, Fatima Hamidu, Mustapha Abdul Mumin Mohammed, Ayuba Nii Darku Ankrah, Seth Kwabena Amponsah   +8 more
wiley   +1 more source

Stemness-based gastric cancer classification by machine learning for precision diagnosis and treatment of gastric cancer. [PDF]

J Gastrointest Oncol
Zhou S, Tian C, Zhu T, Chen H, Chen C, Jiang Q, Liu F.   +6 more
europepmc   +1 more source

Prognostic Impact of European LeukemiaNet Genetic Risk Stratification System in Adult Patients With Acute Myeloid Leukemia

Aging and Cancer, EarlyView.
This study aimed to evaluate the prognostic value of ELN2017 in predicting survival outcomes and to assess the impact of clinical and molecular factors such as age, FLT3 and NPM1 mutations, and allogeneic hematopoietic stem cell transplantation (allo‐HSCT).
Mobina Shrestha, Bishwas Mandal, Vishal Mandal, Asis Shrestha, Amir Babu Shrestha   +4 more
wiley   +1 more source