[HTML][HTML] Informing immunotherapy with multi-omics driven machine learning

Y Li, X Wu, D Fang, Y Luo - npj Digital Medicine, 2024 - nature.com
Progress in sequencing technologies and clinical experiments has revolutionized
immunotherapy on solid and hematologic malignancies. However, the benefits of …

[HTML][HTML] A study of the recent trends of immunology: Key challenges, domains, applications, datasets, and future directions

S Pandya, A Thakur, S Saxena, N Jassal, C Patel… - Sensors, 2021 - mdpi.com
The human immune system is very complex. Understanding it traditionally required
specialized knowledge and expertise along with years of study. However, in recent times …

[HTML][HTML] A nomogram model for predicting 5-year risk of prediabetes in Chinese adults

Y Hu, Y Han, Y Liu, Y Cui, Z Ni, L Wei, C Cao, H Hu… - Scientific Reports, 2023 - nature.com
Early identification is crucial to effectively intervene in individuals at high risk of developing
pre-diabetes. This study aimed to create a personalized nomogram to determine the 5-year …

[HTML][HTML] A pan-cancer analysis of predictive methylation signatures of response to cancer immunotherapy

B Xu, M Lu, L Yan, M Ge, Y Ren, R Wang… - Frontiers in …, 2021 - frontiersin.org
Recently, tumor immunotherapy based on immune checkpoint inhibitors (ICI) has been
introduced and widely adopted for various tumor types. Nevertheless, tumor immunotherapy …

[HTML][HTML] Machine learning for predicting the 3-year risk of incident diabetes in Chinese adults

Y Wu, H Hu, J Cai, R Chen, X Zuo, H Cheng… - Frontiers in Public …, 2021 - frontiersin.org
Purpose: We aimed to establish and validate a risk assessment system that combines
demographic and clinical variables to predict the 3-year risk of incident diabetes in Chinese …

[HTML][HTML] Predicting cancer drug response in vivo by learning an optimal feature selection of tumour molecular profiles

LC Nguyen, S Naulaerts, A Bruna, G Ghislat… - Biomedicines, 2021 - mdpi.com
(1) Background: Inter-tumour heterogeneity is one of cancer's most fundamental features.
Patient stratification based on drug response prediction is hence needed for effective anti …

[HTML][HTML] Predicting cancer drug TARGETS-treatment response generalized elastic-neT signatures

NR Rydzewski, E Peterson, JM Lang, M Yu… - NPJ genomic …, 2021 - nature.com
We are now in an era of molecular medicine, where specific DNA alterations can be used to
identify patients who will respond to specific drugs. However, there are only a handful of …

[HTML][HTML] Multi-approach bioinformatics analysis of curated omics data provides a gene expression panorama for multiple cancer types

BC Feltes, JF Poloni, IJG Nunes, SS Faria… - Frontiers in genetics, 2020 - frontiersin.org
Studies describing the expression patterns and biomarkers for the tumoral process increase
in number every year. The availability of new datasets, although essential, also creates a …

An artificial intelligence model to predict survival and chemotherapy benefits for gastric cancer patients after gastrectomy development and validation in international …

X Li, Z Zhai, W Ding, L Chen, Y Zhao, W Xiong… - International journal of …, 2022 - Elsevier
Background Gastric cancer (GC) is a major health problem worldwide, with high prevalence
and mortality. The present GC staging system provides inadequate prognostic information …

[HTML][HTML] Collaborative study from the Bladder Cancer Advocacy Network for the genomic analysis of metastatic urothelial cancer

JS Damrauer, W Beckabir, J Klomp, M Zhou… - Nature …, 2022 - nature.com
Abstract Urothelial Cancer-Genomic Analysis to Improve Patient Outcomes and Research
(NCT02643043), UC-GENOME, is a genomic analysis and biospecimen repository study in …