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Keywords: machine learning
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Emerg Top Life Sci (2021) 5 (6): 729–745.
Published: 20 December 2021
.... Machine learning approaches, including decision tree methods of Random Forest and XGBoost, and deep learning techniques including deep multi-layer and recurrent neural networks, afford unique capabilities to accurately create predictions from high dimensional, multimodal data. Furthermore, AI methods...
Includes: Supplementary data
Emerg Top Life Sci (2021) 5 (6): 837–847.
Published: 10 December 2021
... of merging the two, providing the scientific community with tools towards observing, understanding, and predicting cellular and tissue phenotypes and behaviors. Furthermore, multiplexed single-cell imaging and machine learning algorithms now enable patient stratification and predictive diagnostics...
Emerg Top Life Sci (2021) 5 (6): 765–777.
Published: 09 December 2021
... to study the etiology and progression of this disease. Meanwhile, the vast amount of data from various modalities, such as genetics, proteomics, transcriptomics, and imaging, as well as clinical features impose great challenges in data integration and analysis. Machine learning (ML) methods offer novel...
Includes: Supplementary data
Emerg Top Life Sci (2021) 5 (6): 757–764.
Published: 07 December 2021
... by Portland Press Limited on behalf of the Biochemical Society and the Royal Society of Biology and distributed under the Creative Commons Attribution License 4.0 (CC BY-NC-ND) . artificial intelligence clinical decision making machine learning next-generation sequencing precision oncology...
Emerg Top Life Sci (2021) 5 (6): 789–802.
Published: 19 October 2021
... are storing increasing amounts of protein structural data, in addition to modeled structures becoming increasingly available. This, combined with the recent advances in graph-based machine-learning models, enables the use of protein structural data in predictive models, with the goal of creating tools...
Emerg Top Life Sci (2021) 5 (1): 113–125.
Published: 09 April 2021
... Intelligence (AI) and Machine Learning (ML) have great potential to revolutionize smart enzyme engineering without the explicit need for a complete understanding of the underlying molecular system. Here, we portray the role and position of AI techniques in the field of enzyme engineering along with their scope...
Emerg Top Life Sci (2021) 5 (1): 13–27.
Published: 07 April 2021
... applications. However, recent technological advancements, along with parallel surge in clinical research have led to the concomitant establishment of other powerful computational techniques such as Artificial Intelligence (AI) and Machine Learning (ML). These leading-edge tools with the ability to successfully...
Emerg Top Life Sci (2019) 3 (6): 741–746.
Published: 14 November 2019
... – Global AIDS Update 2019 , UNAIDS , Geneva 12 World Health Organisation (WHO) . ( 2016 ) Global Action Plan on HIV Drug Resistance 2017–2021 , WHO , Geneva 13 Singh , Y. ( 2017 ) Machine learning to improve the effectiveness of ANRS in predicting HIV drug resistance . Healthc...