Results 41 to 50 of about 2,904,824 (280)

Teleconnection Patterns of Different El Niño Types Revealed by Climate Network Curvature

Geophysical Research Letters, 2022
The diversity of El Niño events is commonly described by two distinct flavors, the Eastern Pacific (EP) and Central Pacific (CP) type. While the remote impacts, that is, teleconnections, of EP and CP events have been studied for different regions ...
Felix M. Strnad, Jakob Schlör, Christian Fröhlich, Bedartha Goswami   +3 more
doaj   +1 more source

Next‐generation proteomics improves lung cancer risk prediction

Molecular Oncology, EarlyView.
This is one of very few studies that used prediagnostic blood samples from participants of two large population‐based cohorts. We identified, evaluated, and validated an innovative protein marker model that outperformed an established risk prediction model and criteria employed by low‐dose computed tomography in lung cancer screening trials.
Megha Bhardwaj, Clara Frick, Ben Schöttker, Bernd Holleczek, Hermann Brenner   +4 more
wiley   +1 more source

Identifying gene-specific subgroups: an alternative to biclustering

BMC Bioinformatics, 2019
Background Transcriptome analysis aims at gaining insight into cellular processes through discovering gene expression patterns across various experimental conditions.
Vincent Branders, Pierre Schaus, Pierre Dupont   +2 more
doaj   +1 more source

Quantitative Assessment of Low-Dose Photodynamic Therapy Effects on Diabetic Wound Healing Using Raman Spectroscopy

Pharmaceutics, 2023
One of challenges that faces diabetes is the wound healing process. The delayed diabetic wound healing is caused by a complicated molecular mechanism involving numerous physiological variables.
Hala Zuhayri, Alice A. Samarinova, Alexey V. Borisov, David A. Lopez Guardado, Houssain Baalbaki, Natalya A. Krivova, Yury V. Kistenev   +6 more
doaj   +1 more source

Tumor mutational burden as a determinant of metastatic dissemination patterns

Molecular Oncology, EarlyView.
This study performed a comprehensive analysis of genomic data to elucidate whether metastasis in certain organs share genetic characteristics regardless of cancer type. No robust mutational patterns were identified across different metastatic locations and cancer types.
Eduardo Candeal, Andrea Moreno‐Manuel, Miguel Salvadó‐Pertierra, Cristina Santos‐Vivas, Rebeca Sanz‐Pamplona   +4 more
wiley   +1 more source

Self-supervision advances morphological profiling by unlocking powerful image representations

Scientific Reports
Cell Painting is an image-based assay that offers valuable insights into drug mechanisms of action and off-target effects. However, traditional feature extraction tools such as CellProfiler are computationally intensive and require frequent parameter ...
Vladislav Kim, Nikolaos Adaloglou, Marc Osterland, Flavio M. Morelli, Marah Halawa, Tim König, David Gnutt, Paula A. Marin Zapata   +7 more
doaj   +1 more source

Contour-Aware Polyp Segmentation in Colonoscopy Images Using Detailed Upsampling Encoder-Decoder Networks

IEEE Access, 2020
Colorectal cancer has become one of the most common cause of cancer mortality worldwide, with a five-year survival rate of over 50%. Additionally, the potential of some common polyp types to progress to colorectal cancer is considered high.
Ngoc-Quang Nguyen, Duc My Vo, Sang-Woong Lee   +2 more
doaj   +1 more source

Study and Observation of the Variation of Accuracies of KNN, SVM, LMNN, ENN Algorithms on Eleven Different Datasets from UCI Machine Learning Repository

, 2018
Machine learning qualifies computers to assimilate with data, without being solely programmed [1, 2]. Machine learning can be classified as supervised and unsupervised learning.
Arif, Rezoana Bente, Khan, Mohammad Mahmudur Rahman, Oishe, Mahjabin Rahman, Siddique, Md. Abu Bakr   +3 more
core   +1 more source

Is Machine Learning Real Learning?

Center for Educational Policy Studies Journal, 2019
The question of whether machine learning is real learning is ambiguous, because the term “real learning” can be understood in two different ways. Firstly, it can be understood as learning that actually exists and is, as such, opposed to something that only appears to be learning, or is misleadingly called learning despite being something else ...
openaire   +5 more sources

Machine learning as ecology

Journal of Physics A: Mathematical and Theoretical, 2020
Machine learning methods have had spectacular success on numerous problems. Here we show that a prominent class of learning algorithms - including Support Vector Machines (SVMs) -- have a natural interpretation in terms of ecological dynamics. We use these ideas to design new online SVM algorithms that exploit ecological invasions, and benchmark ...
Owen Howell, Cui Wenping, Robert Marsland, Pankaj Mehta   +3 more
openaire   +4 more sources