Prescriptions

Effective prediction of short hydrogen bonds in proteins via machine learning method.

Short hydrogen bonds (SHBs), whose donor and acceptor heteroatoms lie within 2.7 Å, exhibit prominent quantum mechanical characters and are connected to a wide range of essential biomolecular processes. However, exact determination of the geometry and functional roles of SHBs requires a protein to be at atomic resolution. In this work, we analyze 1260 high-resolution peptide and protein structures...

An annotated corpus from biomedical articles to construct a drug-food interaction database.

MOTIVATION: While drug-food interaction (DFI) may undermine the efficacy and safety of drugs, DFI detection has been difficult because a well-organized database for DFI did not exist. To construct a DFI database and build a natural language processing system extracting DFI from biomedical articles, we formulated the DFI extraction tasks and manually annotated texts that could have contained DFI in...

A novel graph convolutional neural network for predicting interaction sites on protein kinase inhibitors in phosphorylation.

Protein kinase-inhibitor interactions are key to the phosphorylation of proteins involved in cell proliferation, differentiation, and apoptosis, which...

Assessment of a hybrid decision support system using machine learning with artificial intelligence to safely rule out prescriptions from medication review in daily practice.

Background Medication review is time-consuming and not exhaustive in most French hospitals. We routinely use an innovative hybrid decision support sys...

Construction of a prediction model for drug removal rate in hemodialysis based on chemical structures.

In designing drug dosing for hemodialysis patients, the removal rate (RR) of the drug by hemodialysis is important. However, acquiring the RR is diffi...

Super.Complex: A supervised machine learning pipeline for molecular complex detection in protein-interaction networks.

Characterization of protein complexes, i.e. sets of proteins assembling into a single larger physical entity, is important, as such assemblies play ma...

A Data-Driven Iterative Approach for Semi-automatically Assessing the Correctness of Medication Value Sets: A Proof of Concept Based on Opioids.

BACKGROUND: Value sets are lists of terms (e.g., opioid medication names) and their corresponding codes from standard clinical vocabularies (e.g., RxN...

Is Blood Loss Greater in Elderly Patients under Antiplatelet or Anticoagulant Medication for Cervical Spine Injury Surgery? A Japanese Multicenter Survey.

INTRODUCTION: In elderly patients with cervical spinal cord injury, comorbidities such as cardiovascular and cerebrovascular diseases are common, with...

Safe medicine recommendation via star interactive enhanced-based transformer model.

With the rapid development of electronic medical records (EMRs), most existing medicine recommendation systems based on EMRs explore knowledge from th...

Machine learning in systematic reviews: Comparing automated text clustering with Lingo3G and human researcher categorization in a rapid review.

Systematic reviews are resource-intensive. The machine learning tools being developed mostly focus on the study identification process, but tools to a...

In Vitro Cytotoxicity and Anti-HIV Activity of Crude Extracts of , and .

INTRODUCTION: Human immunodeficiency virus (HIV) affects the body's defense mechanisms and leads to a number of opportunistic infections which later c...

Machine learning prediction of antiviral-HPV protein interactions for anti-HPV pharmacotherapy.

Persistent infection with high-risk types Human Papillomavirus could cause diseases including cervical cancers and oropharyngeal cancers. Nonetheless,...

Sensors and Artificial Intelligence Methods and Algorithms for Human-Computer Intelligent Interaction: A Systematic Mapping Study.

To equip computers with human communication skills and to enable natural interaction between the computer and a human, intelligent solutions are requi...

Evaluation of Glucocorticoid Therapy in Asthma Children with Small Airway Obstruction Based on CT Features of Deep Learning.

This study was aimed at exploring the treatment of asthma children with small airway obstruction in CT imaging features of deep learning and glucocort...

Real-Time Detection of Concealed Threats with Passive Millimeter Wave and Visible Images via Deep Neural Networks.

Passive millimeter wave has been employed in security inspection owing to a good penetrability to clothing and harmlessness. However, the passive mill...

A Target Detection Algorithm for Remote Sensing Images Based on Deep Learning.

In order to improve the accuracy of remote sensing image target detection, this paper proposes a remote sensing image target detection algorithm DFS b...

A New Socially Assistive Robot with Integrated Serious Games for Therapies with Children with Autism Spectrum Disorder and Down Syndrome: A Pilot Study.

This work introduces a new socially assistive robot termed MARIA T21 (meaning "Mobile Autonomous Robot for Interaction with Autistics", with the addit...

Stand-Alone Use of Artificial Intelligence for Digital Mammography and Digital Breast Tomosynthesis Screening: A Retrospective Evaluation.

Background Use of artificial intelligence (AI) as a stand-alone reader for digital mammography (DM) or digital breast tomosynthesis (DBT) breast scree...

Artificial evolution of robot bodies and control: on the interaction between evolution, learning and culture.

We survey and reflect on how learning (in the form of individual learning and/or culture) can augment evolutionary approaches to the joint optimizatio...

Predictive Model for Drug-Induced Liver Injury Using Deep Neural Networks Based on Substructure Space.

Drug-induced liver injury (DILI) is a major concern for drug developers, regulators, and clinicians. However, there is no adequate model system to ass...