Results 51 to 60 of about 154,891 (246)

Gut microbiome and aging—A dynamic interplay of microbes, metabolites, and the immune system

FEBS Letters, EarlyView.
Age‐dependent shifts in microbial communities engender shifts in microbial metabolite profiles. These in turn drive shifts in barrier surface permeability of the gut and brain and induce immune activation. When paired with preexisting age‐related chronic inflammation this increases the risk of neuroinflammation and neurodegenerative diseases.
Aaron Mehl, Eran Blacher
wiley   +1 more source

Feature importance correlation from machine learning indicates functional relationships between proteins and similar compound binding characteristics

Scientific Reports, 2021
Machine learning is widely applied in drug discovery research to predict molecular properties and aid in the identification of active compounds. Herein, we introduce a new approach that uses model-internal information from compound activity predictions ...
Raquel Rodríguez-Pérez, Jürgen Bajorath   +1 more
doaj   +1 more source

Using Multilingual Bidirectional Encoder Representations from Transformers on Medical Corpus for Kurdish Text Classification

ARO-The Scientific Journal of Koya University, 2023
Technology has dominated a huge part of human life. Furthermore, technology users use language continuously to express feelings and sentiments about things.
Soran S. Badawi
doaj   +1 more source

Machine learning interatomic potential for silicon-nitride (Si3N4) by active learning

The Journal of Chemical Physics, 2023
Silicon nitride (Si3N4) is an extensively used material in the automotive, aerospace, and semiconductor industries. However, its widespread use is in contrast to the scarce availability of reliable interatomic potentials that can be employed to study various aspects of this material on an atomistic scale, particularly its amorphous phase. In this work,
Diego Milardovich, Christoph Wilhelmer, Dominic Waldhoer, Lukas Cvitkovich, Ganesh Sivaraman, Tibor Grasser   +5 more
openaire   +2 more sources

Perspectives in educating molecular pathologists on liquid biopsy: Toward integrative, equitable, and decentralized precision oncology

Molecular Oncology, EarlyView.
Liquid biopsy enables minimally invasive, real‐time molecular profiling through analysis of circulating biomarkers in biological fluids. This Perspective highlights the importance of training pathologists through integrative educational programs, such as the European Masters in Molecular Pathology, to ensure effective and equitable implementation of ...
Marius Ilié, Umberto Malapelle, Catherine Alix‐Panabières, Claus Lindbjerg Andersen, Sandra Chlebowski, Vivien Lake, Caroline Lacoux, Virginie Lespinet‐Fabre, Olivier Bordone, Simon Heeke, Christophe Bontoux, Ellen Heitzer, Klaus Pantel, Paul Hofman   +13 more
wiley   +1 more source

Supervised machine learning and active learning in classification of radiology reports [PDF]

Journal of the American Medical Informatics Association, 2014
This paper presents an automated system for classifying the results of imaging examinations (CT, MRI, positron emission tomography) into reportable and non-reportable cancer cases. This system is part of an industrial-strength processing pipeline built to extract content from radiology reports for use in the Victorian Cancer Registry.In addition to ...
Dung H M, Nguyen, Jon D, Patrick
openaire   +2 more sources

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

RaMBat: Accurate identification of medulloblastoma subtypes from diverse data sources with severe batch effects

Molecular Oncology, EarlyView.
To integrate multiple transcriptomics data with severe batch effects for identifying MB subtypes, we developed a novel and accurate computational method named RaMBat, which leveraged subtype‐specific gene expression ranking information instead of absolute gene expression levels to address batch effects of diverse data sources.
Mengtao Sun, Jieqiong Wang, Shibiao Wan
wiley   +1 more source

Prediction of Emergency Cesarean Section Using Machine Learning Methods: Development and External Validation of a Nationwide Multicenter Dataset in Republic of Korea

Life, 2022
This study was a multicenter retrospective cohort study of term nulliparous women who underwent labor, and was conducted to develop an automated machine learning model for prediction of emergent cesarean section (CS) before onset of labor.
Jeong Ha Wie, Se Jin Lee, Sae Kyung Choi, Yun Sung Jo, Han Sung Hwang, Mi Hye Park, Yeon Hee Kim, Jae Eun Shin, Ki Cheol Kil, Su Mi Kim, Bong Suk Choi, Hanul Hong, Hyun-Joo Seol, Hye-Sung Won, Hyun Sun Ko, Sunghun Na   +15 more
doaj   +1 more source

Subtype‐specific enhancer RNAs define transcriptional regulators and prognosis in breast cancers

Molecular Oncology, EarlyView.
This study employed machine learning methodologies to perform the subtype‐specific classification of RNA‐seq data sets, which are mapped on enhancers from TCGA‐derived breast cancer patients. Their integration with gene expression (referred to as ProxCReAM eRNAs) and chromatin accessibility profiles has the potential to identify lineage‐specific and ...
Aamena Y. Patel, Peyman Zarrineh, Nathnael T. Tuffa, Jigar H. Sheth, Sumitra Mohan, Mudassar Iqbal, Sankari Nagarajan   +6 more
wiley   +1 more source