Data-driven strategies for accelerated materials design
R Pollice, G dos Passos Gomes… - Accounts of Chemical …, 2021 - ACS Publications
Conspectus The ongoing revolution of the natural sciences by the advent of machine
learning and artificial intelligence sparked significant interest in the material science …
learning and artificial intelligence sparked significant interest in the material science …
Applications of machine learning in drug discovery and development
Drug discovery and development pipelines are long, complex and depend on numerous
factors. Machine learning (ML) approaches provide a set of tools that can improve discovery …
factors. Machine learning (ML) approaches provide a set of tools that can improve discovery …
The Matthews correlation coefficient (MCC) should replace the ROC AUC as the standard metric for assessing binary classification
Binary classification is a common task for which machine learning and computational
statistics are used, and the area under the receiver operating characteristic curve (ROC …
statistics are used, and the area under the receiver operating characteristic curve (ROC …
Development of a clinical polygenic risk score assay and reporting workflow
Implementation of polygenic risk scores (PRS) may improve disease prevention and
management but poses several challenges: the construction of clinically valid assays …
management but poses several challenges: the construction of clinically valid assays …
Artificial intelligence and machine learning in precision and genomic medicine
S Quazi - Medical Oncology, 2022 - Springer
The advancement of precision medicine in medical care has led behind the conventional
symptom-driven treatment process by allowing early risk prediction of disease through …
symptom-driven treatment process by allowing early risk prediction of disease through …
Optimal classifier for imbalanced data using Matthews Correlation Coefficient metric
Data imbalance is frequently encountered in biomedical applications. Resampling
techniques can be used in binary classification to tackle this issue. However such solutions …
techniques can be used in binary classification to tackle this issue. However such solutions …
Toxicity testing in the 21st century: progress in the past decade and future perspectives
D Krewski, ME Andersen, MG Tyshenko… - Archives of …, 2020 - Springer
Advances in the biological sciences have led to an ongoing paradigm shift in toxicity testing
based on expanded application of high-throughput in vitro screening and in silico methods …
based on expanded application of high-throughput in vitro screening and in silico methods …
CD8 T cell score as a prognostic biomarker for triple negative breast cancer
CD8 T cell is an essential component of tumor-infiltrating lymphocytes (TIL) and tumor
immune microenvironment (TIME). Using the xCell CD8 T cell score of whole tumor gene …
immune microenvironment (TIME). Using the xCell CD8 T cell score of whole tumor gene …
Virtual microdissection identifies distinct tumor-and stroma-specific subtypes of pancreatic ductal adenocarcinoma
RA Moffitt, R Marayati, EL Flate, KE Volmar… - Nature …, 2015 - nature.com
Pancreatic ductal adenocarcinoma (PDAC) remains a lethal disease with a 5-year survival
rate of 4%. A key hallmark of PDAC is extensive stromal involvement, which makes …
rate of 4%. A key hallmark of PDAC is extensive stromal involvement, which makes …
Blood molecular markers associated with COVID‐19 immunopathology and multi‐organ damage
YM Chen, Y Zheng, Y Yu, Y Wang, Q Huang… - The EMBO …, 2020 - embopress.org
COVID‐19 is characterized by dysregulated immune responses, metabolic dysfunction and
adverse effects on the function of multiple organs. To understand host responses to COVID …
adverse effects on the function of multiple organs. To understand host responses to COVID …