Prescriptions

A Deep Learning Model for Cell Growth Inhibition IC50 Prediction and Its Application for Gastric Cancer Patients.

Heterogeneity in intratumoral cancers leads to discrepancies in drug responsiveness, due to diverse genomics profiles. Thus, prediction of drug responsiveness is critical in precision medicine. So far, in drug responsiveness prediction, drugs' molecular "fingerprints", along with mutation statuses, have not been considered. Here, we constructed a 1-dimensional convolution neural network model, Dee...

Medication-rights detection using incident reports: A natural language processing and deep neural network approach.

Medication errors often occurred due to the breach of medication rights that are the right patient, the right drug, the right time, the right dose and the right route. The aim of this study was to develop a medication-rights detection system using natural language processing and deep neural networks to automate medication-incident identification using free-text incident reports. We assessed the pe...

Deciphering interaction fingerprints from protein molecular surfaces using geometric deep learning.

Predicting interactions between proteins and other biomolecules solely based on structure remains a challenge in biology. A high-level representation ...

Evolving multilayer perceptron, and factorial design for modelling and optimization of dye decomposition by bio-synthetized nano CdS-diatomite composite.

Design of experiment and hybrid genetic algorithm optimized multilayer perceptron (GA-MLP) artificial neural network have been employed to model and p...

Interaction of apigenin-7-O-glucoside with pyrimethamine against growth.

Apigenin-7-O-glucoside, a flavonoid glucoside known to inhibit cancer cell growth, fungi growth, both intra and extracellular reactive oxygen species ...

[Predicting atrial fibrillation through a sinus-rhythm electrocardiogram; useful or not?].

In patients with cryptogenic stroke, the detection of atrial fibrillation (AF) is important, since it is an indication for the prescription of oral an...

CURATE.AI: Optimizing Personalized Medicine with Artificial Intelligence.

The clinical team attending to a patient upon a diagnosis is faced with two main questions: what treatment, and at what dose? Clinical trials' results...

DualWMDR: Detecting epistatic interaction with dual screening and multifactor dimensionality reduction.

Detecting epistatic interaction is a typical way of identifying the genetic susceptibility of complex diseases. Multifactor dimensionality reduction (...

The Effect of Optic Flow Speed on Active Participation During Robot-Assisted Treadmill Walking in Healthy Adults.

This study aimed to investigate: 1) the effect of optic flow speed manipulation on active participation during robot-assisted treadmill walking (RATW)...

On semiparametric estimation of a path-specific effect in the presence of mediator-outcome confounding.

Path-specific effects constitute a broad class of mediated effects from an exposure to an outcome via one or more causal pathways along a set of inter...

An Overview of Machine Learning and Big Data for Drug Toxicity Evaluation.

Drug toxicity evaluation is an essential process of drug development as it is reportedly responsible for the attrition of approximately 30% of drug ca...

A simple knowledge-based tool for stereotactic radiosurgery pre-planning.

We studied the dosimetry of single-isocenter treatment plans generated to treat a solitary intracranial lesion using linac-based stereotactic radiosur...

A Bayesian machine learning approach for drug target identification using diverse data types.

Drug target identification is a crucial step in development, yet is also among the most complex. To address this, we develop BANDIT, a Bayesian machin...

The assessment of efficient representation of drug features using deep learning for drug repositioning.

BACKGROUND: De novo drug discovery is a time-consuming and expensive process. Nowadays, drug repositioning is utilized as a common strategy to discove...

Comparative analysis on Facebook post interaction using DNN, ELM and LSTM.

This study presents a novel research approach to predict user interaction for social media post using machine learning algorithms. The posts are conve...

Multifunctional Nanorobot System for Active Therapeutic Delivery and Synergistic Chemo-photothermal Therapy.

Nanorobots are safe and exhibit powerful functionalities, including delivery, therapy, and diagnosis. Therefore, they are in high demand for the devel...

In-Silico Molecular Binding Prediction for Human Drug Targets Using Deep Neural Multi-Task Learning.

In in-silico prediction for molecular binding of human genomes, promising results have been demonstrated by deep neural multi-task learning due to its...

ARPNet: Antidepressant Response Prediction Network for Major Depressive Disorder.

Treating patients with major depressive disorder is challenging because it takes several months for antidepressants prescribed for the patients to tak...

ADMET Evaluation in Drug Discovery. 19. Reliable Prediction of Human Cytochrome P450 Inhibition Using Artificial Intelligence Approaches.

Adverse effects induced by drug-drug interactions may result in early termination of drug development or even withdrawal of drugs from the market, and...

Predictors of adherence to nicotine replacement therapy: Machine learning evidence that perceived need predicts medication use.

BACKGROUND: Nonadherence to smoking cessation medication is a frequent problem. Identifying pre-quit predictors of nonadherence may help explain nonad...