Interpretable and explainable machine learning: a methods‐centric overview with concrete examples
R Marcinkevičs, JE Vogt - Wiley Interdisciplinary Reviews: Data …, 2023 - Wiley Online Library
Interpretability and explainability are crucial for machine learning (ML) and statistical
applications in medicine, economics, law, and natural sciences and form an essential …
applications in medicine, economics, law, and natural sciences and form an essential …
Review on interpretable machine learning in smart grid
In recent years, machine learning, especially deep learning, has developed rapidly and has
shown remarkable performance in many tasks of the smart grid field. The representation …
shown remarkable performance in many tasks of the smart grid field. The representation …
Explainable AI for glaucoma prediction analysis to understand risk factors in treatment planning
Glaucoma causes irreversible blindness. In 2020, about 80 million people worldwide had
glaucoma. Existing machine learning (ML) models are limited to glaucoma prediction, where …
glaucoma. Existing machine learning (ML) models are limited to glaucoma prediction, where …
Explainable AI for machine fault diagnosis: understanding features' contribution in machine learning models for industrial condition monitoring
Although the effectiveness of machine learning (ML) for machine diagnosis has been widely
established, the interpretation of the diagnosis outcomes is still an open issue. Machine …
established, the interpretation of the diagnosis outcomes is still an open issue. Machine …
The benefits and pitfalls of machine learning for biomarker discovery
Prospects for the discovery of robust and reproducible biomarkers have improved
considerably with the development of sensitive omics platforms that can enable …
considerably with the development of sensitive omics platforms that can enable …
Artificial Immune Cell, AI‐cell, a New Tool to Predict Interferon Production by Peripheral Blood Monocytes in Response to Nucleic Acid Nanoparticles
M Chandler, S Jain, J Halman, E Hong… - Small, 2022 - Wiley Online Library
Nucleic acid nanoparticles, or NANPs, rationally designed to communicate with the human
immune system, can offer innovative therapeutic strategies to overcome the limitations of …
immune system, can offer innovative therapeutic strategies to overcome the limitations of …
A systematic review of biologically-informed deep learning models for cancer: fundamental trends for encoding and interpreting oncology data
Background There is an increasing interest in the use of Deep Learning (DL) based
methods as a supporting analytical framework in oncology. However, most direct …
methods as a supporting analytical framework in oncology. However, most direct …
[HTML][HTML] The promise of explainable deep learning for omics data analysis: Adding new discovery tools to AI
M Santorsola, F Lescai - New Biotechnology, 2023 - Elsevier
Deep learning has already revolutionised the way a wide range of data is processed in
many areas of daily life. The ability to learn abstractions and relationships from …
many areas of daily life. The ability to learn abstractions and relationships from …
[HTML][HTML] Opportunities for basic, clinical, and bioethics research at the intersection of machine learning and genomics
The data-intensive fields of genomics and machine learning (ML) are in an early stage of
convergence. Genomics researchers increasingly seek to harness the power of ML methods …
convergence. Genomics researchers increasingly seek to harness the power of ML methods …
[HTML][HTML] A comprehensive overview of microbiome data in the light of machine learning applications: categorization, accessibility, and future directions
Metagenomics, Metabolomics, and Metaproteomics have significantly advanced our
knowledge of microbial communities by providing culture-independent insights into their …
knowledge of microbial communities by providing culture-independent insights into their …