Accessible Machine Learning Approaches for Toxicology

This article describes the DataBox project which offers a perspective of a new health data management solution in Germany. DataBox was initially conceptualized as a repository of individual lung cancer patient data (structured and unstructured). The patient is the owner of the data and is able to share his or her data with different stakeholders. Data is transferred, displayed, and stored online, but not archived. In the long run, the project aims at replacing the conventional method of paper- and storage-device-based handling of data for all patients in Germany, leading to better organization and availability of data which reduces duplicate diagnostic procedures, treatment errors, and enables the training as well as usage of artificial intelligence algorithms on large datasets.

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A novel ensemble based recommendation approach using network based analysis for identification of effective drugs for Tuberculosis

Haldar¹,

Narayanan²

2021

MBE

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<abstract> <p>Tuberculosis (TB) is a fatal infectious disease which affected millions of people worldwide for many decades and now with mutating drug resistant strains, it poses bigger challenges in treatment of the patients. Computational techniques might play a crucial role in rapidly developing new or modified anti-tuberculosis drugs which can tackle these mutating strains of TB. This research work applied a computational approach to generate a unique recommendation list of possible TB drugs as an alternate to a popular drug, EMB, by first securing an initial list of drugs from a popular online database, PubChem, and thereafter applying an ensemble of ranking mechanisms. As a novelty, both the pharmacokinetic properties and some network based attributes of the chemical structure of the drugs are considered for generating separate recommendation lists. The work also provides customized modifications on a popular and traditional ensemble ranking technique to cater to the specific dataset and requirements. The final recommendation list provides established chemical structures along with their ranks, which could be used as alternatives to EMB. It is believed that the incorporation of both pharmacokinetic and network based properties in the ensemble ranking process added to the effectiveness and relevance of the final recommendation.</p> </abstract>

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Accessible Machine Learning Approaches for Toxicology

Cited by 3 publications

References 93 publications

Machine learning models for predicting endocrine disruption potential of environmental chemicals

Machine learning models for predicting endocrine disruption potential of environmental chemicals

Patient-Centered Mobile Health Data Management Solution for the German Health Care System (The DataBox Project)

A novel ensemble based recommendation approach using network based analysis for identification of effective drugs for Tuberculosis

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