PTML multi-label algorithms: models, software, and applications
B Ortega-Tenezaca, V Quevedo-Tumailli… - Current Topics in …, 2020 - ingentaconnect.com
By combining Machine Learning (ML) methods with Perturbation Theory (PT), it is possible
to develop predictive models for a variety of response targets. Such combination often …
to develop predictive models for a variety of response targets. Such combination often …
Risk assessment of veterinary drug residues in meat products
H Zhang, Q Chen, B Niu - Current Drug Metabolism, 2020 - ingentaconnect.com
With the improvement of the global food safety regulatory system, there is an increasing
importance for food safety risk assessment. Veterinary drugs are widely used in poultry and …
importance for food safety risk assessment. Veterinary drugs are widely used in poultry and …
Designing nanoparticle release systems for drug–vitamin cancer co-therapy with multiplicative perturbation-theory machine learning (PTML) models
Nano-systems for cancer co-therapy including vitamins or vitamin derivatives have showed
adequate results to continue with further research studies to better understand them …
adequate results to continue with further research studies to better understand them …
PTML model for selection of nanoparticles, anticancer drugs, and vitamins in the design of drug–vitamin nanoparticle release systems for cancer cotherapy
Nanosystems are gaining momentum in pharmaceutical sciences because of the wide
variety of possibilities for designing these systems to have specific functions. Specifically …
variety of possibilities for designing these systems to have specific functions. Specifically …
PTML model of ChEMBL compounds assays for vitamin derivatives
Determining the biological activity of vitamin derivatives is needed given that organic
synthesis of analogs of vitamins is an active field of interest for medicinal chemistry …
synthesis of analogs of vitamins is an active field of interest for medicinal chemistry …
Machine learning guided prediction of warfarin blood levels for personalized medicine based on clinical longitudinal data from cardiac surgery patients: a prospective …
Background: Warfarin is a common oral anticoagulant, and its effects vary widely among
individuals. Numerous dose-prediction algorithms have been reported based on cross …
individuals. Numerous dose-prediction algorithms have been reported based on cross …
Machine learning as a proposal for a better application of food nanotechnology regulation in the European Union
Aims: Given the current gaps of scientific knowledge and the need of efficient application of
food law, this paper makes an analysis of principles of European food law for the …
food law, this paper makes an analysis of principles of European food law for the …
Implementación y optimización de algoritmos para aprendizaje automático con teoría de perturbaciones
DB Ortega Tenezaca - 2023 - ruc.udc.es
En la actualidad se ha acumulado una ingente cantidad de datos relacionados con
sistemas complejos de muy variada indole: biomoleculares, economicos, sociales, etc …
sistemas complejos de muy variada indole: biomoleculares, economicos, sociales, etc …
[PDF][PDF] 5) Modelling Vitamin Derivatives
I Newton - Ricardo Santana Cabello, 2021 - repository.upb.edu.co
Determining the biological activity of vitamins derivatives is needed given that organic
synthesis of analogs of vitamins is an active field of interest for Medicinal Chemistry …
synthesis of analogs of vitamins is an active field of interest for Medicinal Chemistry …
[PDF][PDF] Predictive Modeling with Machine Learning and Perturbation Theory
B Ortega-Tenezaca, V Quevedo-Tumailli - 2021 - sciforum.net
PTML is a combination of Machine Learning (ML) and Perturbation Theory (PT) that allows
to create prediction models in many areas of knowledge mainly in Medicinal Chemistry to …
to create prediction models in many areas of knowledge mainly in Medicinal Chemistry to …